HK1190474A - Search assistant system and method - Google Patents

Abstract

Disclosed is a system and method for presenting content in response to receiving a portion of a search query. A computing device receives, over a network from a user computer, a portion of a search query submitted by a user in a search query entry area. The computing device receives, from a search suggestion module, one or more search suggestions related to the portion of the query. The computing device transmits, to the user computer, the one or more search suggestions for display in a search suggestion region, the search suggestion region displayed differently than a search results area. The computing device transmits a search suggestion of the one or more search suggestions to a rich content module. The rich content module generates rich content related to the transmitted search suggestion. The computing device transmits, to the user computer, the rich content for display in the search suggestion region.

Description

Search assistance system and method

Technical Field

The present disclosure relates to searching over a network, and more particularly, to content presented in response to a received partial search query.

Background

Currently, because of the large amount of information on the network, it is difficult to filter or quickly find the correct content or the most relevant content that the user finds. Users are often targeted and generally require fast and simple solutions. For example, a search for the latest product to purchase may include accessing multiple pages and multiple reformulations of the search query before satisfactory results are obtained. Also, search engines typically limit their results to the traditional ten links on the search results web page. It is often difficult for a user to find his or her answers to a query without performing multiple searches via multiple search engine queries.

Disclosure of Invention

The present disclosure provides rich content in a search suggestion region when a user enters a search query in a search query entry area. This helps to reduce the burden of search results as described above.

In one aspect, a computing device receives, over a network, alphanumeric characters forming a portion of a search query submitted by a user in a search query entry area from a user computer. The computing device receives one or more search suggestions related to the partial search query from the search suggestion module. Prior to initiating a search query via user input, the computing device transmits one or more search suggestions to the user computer for display by the user computer in a search suggestion region, the search suggestion region being displayed differently than the search results region. The computing device transmits one of the one or more search suggestions to the rich content module. The rich content module generates rich content related to the transmitted search suggestion. Prior to initiating a search query via user input, the computing device transmits rich content to the user computer for display in the search suggestion region.

In one embodiment, transmitting the search suggestion to a rich content module further comprises: classifying, by the rich content module, the search suggestion into a category. In one embodiment, the classification is based on classification techniques such as a fixed priority order, query classification confidence, use of the user's search session context, use of the user's search history profile, and the like.

In one embodiment, the receiving of the rich content further comprises: and erasing the network of the rich content. This may be performed when the computing device is in a non-communicating state with the user computer. The rich content may also be received from a database. In one embodiment, search engine logs are mined by classifying queries in the logs into one or more categories. In one embodiment, a relationship is generated, such as a query-to-query relationship and/or a query-to-search-result relationship. In one embodiment, social network feedback is used.

In one embodiment, the transmitting of the rich content further comprises: the advertisement is transmitted as part of the rich content. In one embodiment, sponsored search suggestions are transmitted as part of the one or more search suggestions. In one embodiment, the one or more search suggestions are updated as additional alphanumeric characters are entered by the user in the search query entry area. In one embodiment, the rich content is updated as additional alphanumeric characters are entered by the user in the search query entry area.

In another aspect, a computing device includes a network interface for receiving, over a network, alphanumeric characters forming a portion of a search query submitted by a user in a search query entry area from a user computer. A search suggestion module of a computing device to generate one or more search suggestions related to the partial search query, wherein the network interface transmits the one or more search suggestions to the user computer for display by the user computer in a search suggestion region prior to initiating the search query via user input. In one embodiment, the search suggestion region is displayed differently than the search results area. A rich content module of the computing device to receive a search suggestion of the one or more search suggestions and generate rich content related to the transmitted search suggestion. In one embodiment, the network interface transmits the rich content to the user computer for display by the user computer in a search suggestion region prior to initiating the search query via user input.

These and other methods and embodiments will be apparent to those of ordinary skill in the art by reference to the following detailed description and accompanying drawings.

Drawings

In the drawings (which are not necessarily drawn to scale and wherein like reference numerals represent like elements throughout the several views):

FIG. 1A is a block diagram of a user computer in communication with a server computer over a network according to an embodiment of the present disclosure;

FIG. 1B is a block diagram of a search suggestion region displayed by the user computer of FIG. 1A;

FIG. 2 is a flowchart illustrating steps performed by the server computer of FIG. 1A in accordance with an embodiment of the present disclosure;

FIG. 3 is a block diagram of modules in communication with the server computer of FIG. 1A, according to an embodiment of the present disclosure;

FIG. 4 is a flowchart illustrating steps performed by the server computer of FIG. 1A in accordance with an embodiment of the present disclosure;

FIG. 5 is a block diagram of a system implementing the steps described in FIGS. 2 and 4 in accordance with an embodiment of the present disclosure;

FIG. 6 is a block diagram of a system implementing the steps described in FIGS. 2 and 4 in accordance with an embodiment of the present disclosure;

FIG. 7 is a block diagram of a system for determining search suggestions according to an embodiment of the present disclosure;

FIG. 8 is a screen shot of a web page with rich content according to an embodiment of the present disclosure;

9A-9F are screenshots of a web page with rich content and search suggestions that are updated as the search query changes, according to embodiments of the present disclosure;

FIG. 10 is a screen shot of a web page with rich content according to an embodiment of the present disclosure; and

fig. 11 is a block diagram illustrating an internal architecture of a computing device according to an embodiment of the present disclosure.

Detailed Description

Embodiments will now be described in more detail with reference to the drawings of the present application. In the drawings, like and/or corresponding elements are referred to by like reference numerals.

Various embodiments are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various forms. In addition, each of the examples given in connection with the various embodiments is intended to be illustrative, and not restrictive. Moreover, the figures are not necessarily to scale, some features may be exaggerated to show details of particular components (and any dimensions, materials, and similar details shown in the figures are intended to be illustrative and not restrictive). Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the disclosed embodiments.

The present invention is described below in terms of block diagrams and operational illustrations of methods and apparatus for selecting and presenting media related to a particular topic. It will be understood that each block of the block diagrams, and combinations of blocks in the block diagrams or operational illustrations, can be implemented by analog or digital hardware and computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, ASIC, or other programmable data processing apparatus, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, implement the functions/acts specified in the block diagrams or operational block or blocks.

In some alternative implementations, the functions/acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Moreover, method embodiments shown and described in flow charts are provided in this disclosure by way of example for a more complete understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. In a foreseeable alternative embodiment, the order of various operations may be changed, and sub-operations described as part of larger operations may be performed independently.

FIG. 1A is a diagram of a system for interacting with a server computer 110, for exampleA block diagram of an embodiment of a user computer 105 communicating over a networked network 115. In one embodiment, a user uses user computer 105 to display web page 117 via web browser 118. Web page 117 (e.g., Yahoo!Or) A search query entry area 125 is included in which a user may enter a partial search query (e.g., one or more alphanumeric characters) or a complete search query (e.g., one or more words).

In one embodiment, a user enters a partial search query (e.g., one or more alphanumeric characters) into search query input area 125. As the user enters the partial search query (or, in another embodiment, thereafter) at search query entry area 125, user computer 105 (browser 118) transmits the partial search query 130 to server computer 110. In response to receiving the partial search query 130, the server computer 110 generates and transmits one or more search suggestions 140 to the user computer 105 for display in the search suggestion region 145. The search suggestions 140 are one or more words related to the partial search query 130. For example, if the user enters "kob" in search query input area 125, the search suggestions displayed by user computer 105 may be "Kobe Bryant" and "Kobe beef". The server computer 110 also transmits the rich content 150 to the user computer 105 for display in the search suggestion region 145 of the web page 117.

Referring again to FIG. 1B, the rich content 150 is structured information related to the search suggestions 140. Using the above example, in one embodiment, if the mouse hovers over the search suggestion 140 "Kobe Bryant," then the rich content 150 includes a photograph of Kobe Bryant, his location, his team, his season average score, links to more information about Kobe Bryant, and the like. Thus, the user does not need to click on the "Search" key on web page 117 to obtain this information, which is automatically displayed next to the corresponding Search suggestion. In one embodiment, the partial search query 130 is a complete word or a portion of a phrase (e.g., some letters of a word). Although described in terms of a partial search query 130, a user may enter a complete search query (e.g., a complete word or phrase) instead, resulting in the same results.

In one embodiment, the rich content 150 is information displayed next to (above, or below) the search suggestion 140 in the search suggestion region 145. Rich content 150 may include text, one or more graphics, one or more web links, one or more icons, one or more pictures, one or more videos (e.g., a video played when a user clicks on a file or link associated with the video), one or more audio tracks (e.g., a song played when a user clicks on a file or link associated with the song), one or more answers to a question, and so forth.

The search suggestion region 145 is an area of the web page that is different from the area containing the search results of the search. In one embodiment, the search suggestion region 145 may overlap, be located above, below, or beside the area containing the search results. The area containing search results is generally an area containing search results for a search query or a portion of a search query, where the search results include a plurality of web site links and a brief textual description associated with each web site. For example, GoogleIs a service that returns search results for a complete search query or a partial search query to a search results area. The search results are located below the search query input area and the search results are a plurality of links related to web pages that may be relevant to the search query or a portion of the search query. As described in more detail below, the display is shownThe search suggestion region 145 of the rich content 150 (and search suggestions 140) is a separate region from the region containing the search results. In one embodiment, the user may change the size, location, and/or shape of the search suggestion region 145.

In addition, the search suggestion region 145 may be opened or closed by a user or automatically. Additionally, any number of search suggestions and/or rich content segments can be displayed in the search suggestion region 145. For example, although described herein as displaying one piece of rich content for one search suggestion, in another embodiment, a plurality of pieces of rich content corresponding to a plurality of search suggestions are displayed in the search suggestion region 145 (e.g., rich content is displayed for each of the first four search suggestions, where each piece of rich content is divided by a line of the search suggestion region 145). In one embodiment, the rich content segment is capable of displaying a tabbed page (tabbed page). For example, if the query suggestion term "Chicago" is selected, the right panel would be embedded in a tab page where each option represents a different meaning, such as "music play", "travel", etc.

In one embodiment, the server computer 110 is in communication with an advertisement server 160 (shown in phantom). The ad server 160 may be a module or component internal to the server computer 110 or an external module or component. In one embodiment, the server computer 110 transmits the advertisement request 170 to the advertisement server 160. In one embodiment, the request 170 is for advertisements related to the rich content 150 and/or the search suggestion 140. The advertisement server 160 transmits the advertisement 180 to the server computer 110, and the server computer 110 transmits the advertisement 180 as part of the rich content 150 displayed on the user computer 105. In another embodiment, the one or more search suggestions 140 transmitted to the user computer 105 are search suggestions 140 sponsored by a third party. For example, a third party may pay the owner of the server computer 110 to display their search suggestions 140 at particular locations of the list of search suggestions 140.

For the purposes of this disclosure, the term "server" may be understood as a server side that provides the processes, databases, and communication devices. By way of example and not limitation, the term "server" may be one physical processor with associated communication facilities, data storage, and database devices, or may be a networked or clustered complex of processors, associated network and storage devices, and operating software, one or more database systems, and application software, where the complex supports the services provided by the server.

FIG. 2 shows a flowchart illustrating an embodiment of steps performed by the server computer 110. FIG. 3 is a block diagram of an embodiment of modules in communication with server computer 110. As described above, the server computer 110 receives a portion of the search query 130 from the user computer (step 205). In one embodiment, the user's geographic information may be used and transmitted to the server computer 110. In one embodiment, the server computer 110 transmits the portion of the search query 130 to the search suggestion module 305. The search suggestion module 305 determines search suggestions 140 that are relevant to a portion of the search query 130, and/or the user's location, and/or the user's intent as determined by personal preferences or interests stored in the user's search history. In one embodiment, the search suggestion module 305 determines relevant search suggestions 140 based on the user's previous search history. For example, if the user searches for sports-related topics within a predetermined period of time (e.g., within the last two days) and the portion of the search query 130 is "ko", in one embodiment, the search suggestion module 305 determines that the search suggestions 140 should be related to "Kobe Bryant" and not "Kobe beef". Alternatively, if the user searches for restaurants within a predetermined period of time (e.g., within the last two days) and the portion of the search query 130 is "ko", in one embodiment, the search suggestion module 305 determines that the search suggestions 140 should be related to "kobe beef". This personalization may occur at any time period, to one or more users, and may be a selection activated by the user.

In another embodiment, the search suggestion module 305 determines the search suggestions 140 based on the popularity of the search suggestions over a period of time. For example, if "Kobe Bryant" is searched by ten million users within a week and "Kobe beef" is searched by two million users within the same time period, in one embodiment, the search suggestion module 305 displays Kobe Bryant as the first search suggestion or displays various search suggestions related to Kobe Bryant. The "Kobe beef" search suggestion may not be displayed as a search suggestion or may be displayed after multiple "Kobe Bryant" search suggestions (e.g., Kobe Bryant-nba, Kobe Bryant-rodless basket, Kobe Bryant-shoe, etc.).

The search suggestion module 305 transmits the determined search suggestions 140 to the server computer 110. The server computer 110 receives the search suggestions 140 (step 210) and transmits the search suggestions 140 to the user computer (step 215) before the search query is searched (e.g., before the user clicks a search button or before entering his or her full search query and clicking an enter key). In one embodiment, a search suggestion is selected from the plurality of search suggestions 140. In one embodiment, selection of such a search suggestion occurs while the user hovers over the search suggestion using a user cursor. In another embodiment, the selected search suggestion is a user-selected (using a user mouse click) search suggestion. In yet another embodiment, the selected search suggestion is the first (or a predetermined number) search suggestion in the plurality of transmitted search suggestions 140. Although described herein as selecting one search suggestion, in another embodiment, multiple search suggestions 140 may be selected (e.g., the first three search suggestions 140 are selected).

The server computer 110 then transmits the selected search suggestion 310 to the rich content module 320 (step 220). As described above, in one embodiment, the rich content module 320 determines rich content related to the search suggestion 310. For example, when the search suggestion 310 is "Kobe Bryant," the rich content includes a photograph of Kobe Bryant. The rich content module 320 transmits the rich content 150 to the server computer 110. The server computer 110 receives the rich content 150 (step 225). Thereafter, before the search query is searched, the server computer 110 transmits the rich content 150 to the user computer 105 for display (step 230). In one embodiment, the rich content 150 displayed by the user computer 105 is displayed at approximately the same time as the search suggestions 140.

Although shown as distinct modules in FIG. 3, it is noted that one or more of the functions of the modules shown in FIG. 3 may be located external to, internal to, integrated within, etc. server computer 110.

FIG. 4 shows a flowchart of an embodiment of the steps performed by the server computer 110. As described above, the server computer 110 receives a partial search query from a user computer (step 405). In one embodiment, the server computer 110 attempts to detect user intent from the partial search query as the user enters and transmits one or more search suggestions to the user computer for display in the search suggestion region 145 prior to searching the search query (step 410). A search suggestion is selected (e.g., automatically or based on user input) (step 415). The server computer 110 then attempts to detect a search suggestion intent from the selected search suggestions (step 420). The server computer 110 receives the rich content 150 from the rich content module 320 (step 425) and transmits the rich content to the user computer for display in the search suggestion region 145 (step 430).

Fig. 5 is a block diagram of an embodiment of a system 500 to implement the functionality described above. Each component of the system 500 may be a web service or a component. In one embodiment, the search suggestions 310 and the portion of the search query are transmitted to a query classification module 505. In one embodiment, the query classification module 505 classifies the search suggestions 310 into categories, such as "movies," music artists, "" sports stars, "" weather forecasts, "or" tourist attractions. Some search suggestions 310 may be categorized into one category, while others may belong to multiple categories (e.g., the query "Chicago" is both a movie name and a city name).

Based on the suggestion category(s), a different data source needs to be used to obtain the raw data related to the suggestion/category combination 510. For example, for "chicago/movie", movie data such as year, comment, director, actor, etc. is required, but for "chicago/city", city attraction, current affairs, weather forecast, etc. are required. The suggestion/category combination 510 is transmitted to the data federation module 515. The data federation module 515 determines the importance of multiple data sources and obtains data from the respective sources. In one embodiment, data from all categories cannot be used in their entirety. In one embodiment, a category is selected. In one embodiment, the data federation module 515 can select a category using a fixed priority order, query classification confidence, user search session context, and/or user search history profile to determine what the user is more interested in. For example, if the data federation module 515 determines that "movie" is more important, then based on a fixed priority ordering technique, the movie details of "Chicago" may be selected. However, if the data federation module 515 uses the user search history profile, and the user search history profile shows that he or she is a traveler, the city details of "Chicago" will be selected. The data federation module 515 is in communication with a cache layer 520, the cache layer 520 being in communication with any number of vertical back ends (such as vertical back ends 525, 530, 535 shown in FIG. 5), and the wipe and provide services 540, 545 connected to additional (e.g., low speed) vertical back ends 550, 555. In one embodiment, one or more vertical back ends 525, 530, 535, 550, 555 include an environment and a third party back end, among others.

If there is an available vertical database associated with the vertical search engine, rich content for the search suggestions can be obtained by using the vertical search engine or a web service. Such asOrSuch search engines all have their own vertical search engine and database. In another embodiment, the rich content may also be manually entered into one or more databases. If no vertical database is available, then edit input may be used. The rich content may also be retrieved/erased directly from the website. For example, movie data may be automatically obtained from an internet movie database (IMDb) website.

In one embodiment, to ensure low latency, vertical web services (e.g., vertical back ends 525, 530, 535, erase and provide services 540, 545, etc.) are disposed behind the caching layer 520. Queries and responses from the vertical web services 525, 530, 535 will be cached at this layer 520 for a predetermined period of time before they expire. The cache layer 520 is generally faster than the vertical web services 525, 530, 535, 540, 545, 550, 555 because the cache layer 520 does not include complex logic such as index lookup and sorting, etc. If the query is popular enough to have its data available in the cache 520, the overall latency of the system 500 is reduced.

In one embodiment, some vertical web services are not used directly because they are not fast enough. For example, some vertical web services require complex methods to arrange their search results, which can take too much time for system 500 to be used. For these, in one embodiment, a predetermined list of queries that can trigger rich content for the respective category is used, and then the vertical web service can erase the queries in an offline manner. In one embodiment, the erased content is then provided to the key/value lookup server. To ensure that it is up-to-date, the predetermined query list is updated periodically, and the erasure occurs periodically. In one embodiment, the query list is generated by one or more of the following methods: the search engine query logs are mined, editorially generated, or a combination of both by logging queries by the query classification module 505.

In one embodiment, for queries that do not map correctly to a certain category, the system 500 may provide the user with content regarding some idea of the search results, or suggest other queries that may be of interest to the user. These queries are typically longer queries whose query classification approach generally results in a lower confidence index. To provide these types of queries with such content, the system 500 may mine the search engine query logs (via the data mining module 560) and may generate query/query relationships or query/search result relationships in many ways. This analysis may be performed on a cloud computing platform that is capable of handling large amounts of data, such as query logs. In one embodiment, after mining, the data is organized in the form of key/value pairs, where the key is the query itself and the value is the rich content provided for the query. The database may be provided to a low latency key/value lookup service 570. In one embodiment, the mining may be repeated periodically in order to reflect the most recent query relationships. Over time, these relationships can be drastically changed as the user's interests change and may be driven by popular events. By utilizing real-time social network feedback and other data sources, mining can also be conducted in near real-time to provide popular trending events as rich content for users.

In one embodiment, after the syndication module 515 completes obtaining data from the web service and determines the data to use, the data syndication module 515 sends the data to the presentation rendering module 580, and the presentation rendering module 580 transmits the rich content to the user browser for viewing in the search suggestion region 145.

In one embodiment, the rich content may be template-based. In one embodiment, each category has its own template into which the server computer 110 can populate the rich content retrieved from the data federation module 515. In another embodiment, the templates may be dynamically changed to allow for more relevant and dynamic presentation layouts for better user engagement.

Fig. 6 is a block diagram of an embodiment of a system 600 to implement the above-described functionality. As described above, the end user enters a portion of the search query 130, and the user computer 105 transmits the portion 130 to the Front End (FE) 605 of the server computer 110. In one embodiment, FE605 transmits the portion of search query 130 to query suggestion database 610. In one embodiment, query suggestion database 610 returns search suggestions 140 related to the partial query 130 and metadata 615 associated with the search suggestions 140 to FE 605. As described above, the metadata 615 may include: one or more categories associated with each search suggestion, frequency of search suggestions, click information and time, suggested geographic metadata (e.g., Pizza Hut Florham Park has a city name), geographic attributes, and the like. FE605 transmits the one or more search suggestions 310 selected in search suggestion 140 and metadata 620 related to the one or more selected search suggestions 310 to near real-time query intelligence (NRTI) module 625. The NRTI module 625 performs content syndication (e.g., retrieving content from different data sources such as the content data source 630 and/or other data sources 635, where the other data sources 635 include, for example, microblogs, social data, advertisements, user history, etc.). In one embodiment, in offline data processing, data from these data sources 630, 635 is transmitted to a database 640 (e.g., on a grid) or cloud system. In one embodiment, in offline and/or online data publication process 650, data stored on the database 640 (e.g., on a grid) or cloud system is aggregated to NRTI module 625 (arrow 645) and published as rich content 150. In one embodiment, in the offline and/or online data publication process 650, the query/suggestion feedback 665 is transmitted to the query suggestion database 610. In one embodiment, scientific modeling (arrow 655) may also be performed on the data stored in database 640. Scientific modeling may include: query classification, frequency analysis, trend detection, user interest analysis or detection, geographic aggregation, and the like. In one embodiment, the FE605 receives the rich content 150 and transmits the rich content 150 to the content renderer 670 to display the rich content 150 in the search suggestion region 145 of the user computer 105.

FIG. 7 is a block diagram of an embodiment of a system 700 for determining search suggestions. In one embodiment, the FE605 transmits the portion of the search query 130 to the query suggestion meta-service 705. In one embodiment, the query suggestion meta-service 705 communicates with a plurality of data sources to determine search suggestions 140, for example, a eight trigram database 710 including data about celebrities, a local database 715 including data about businesses and website categories, a temporal sense and trend database 720 including data about trending topics (e.g., topics recently searched by people), a depth and event database 725 including data about events, and a deal and coupon database 730 including data about coupons or deals. In one embodiment, if a portion of the search query 130 is not received, the search suggestions 140 (and rich content) provided by the server computer 105 may be trending topics from or related to the time perception and trend database 720.

In one embodiment, the query suggestion meta-service 705 transmits the data feedback 735 to the user database 740, and the user database 740 transmits the aggregated data and the results of the scientific modeling (e.g., user interest analysis and detection (e.g., 30 days ago, 7 days ago, now, etc.), geographic interests, user group interests and trend detection (e.g., age, gender, etc.) to the data publishing process 650. Data publication process 650 publishes the data to databases 710, 715, 720, 725, and 730. In one embodiment, the data publication process 650 publishes the data in near real-time. In one embodiment, the data distribution process 650 also receives vertical data feedback 750 in real-time (or near real-time).

Fig. 8 shows an embodiment of a screenshot of a web page 800. The web page 800 includes a search query entry area 805 that enables a user to enter a search query. In one embodiment, a user enters a partial search query 810 and the search suggestion region 820 displays search suggestions 825 on one side and rich content 830 on the other side before the user taps the enter key or clicks the search button 815. In one embodiment, the first search suggestion 840 is selected (e.g., automatically or by user action). The rich content 830 displayed in the search suggestion region is relevant to the selected first search suggestion 840, as shown by the weather for the next few days of san Carla, Calif. Further, as described above, the search suggestion region 820 overlaps the search results region 850, where the search results region 850 displays the search results of the search. In another embodiment, the search suggestion regions 820 are disposed above, beside, and below the search results area 850. In one embodiment, to display a longer search suggestion, the search suggestions 825 on one side of the search suggestion region 820 are expanded to the right.

Fig. 9A-9F illustrate embodiments of screenshots with rich content 905 displayed next to search suggestions 910 in response to a series of search queries received. Although the final search query is "kobe hybrid," FIGS. 9A-9F illustrate how the search suggestions 910 and rich content 905 are updated as the search query 912 changes. In FIGS. 9B-9F, rich content 905 includes a photograph of kobebryant, his location, and his season mean score. In one embodiment, the rich content 905 may also include data from another service provided by the server computer 110, such as the illustrated forecast (fantasy) tier 915. The rich content 830, 905 shown in FIGS. 8 and 9B-9F includes text and graphics. In another embodiment, referring to fig. 10, the rich content 1005 includes only text, such as movie theaters around a particular city and movie scenes for those theaters.

FIG. 11 is a block diagram illustrating the internal structure of an example computing device, such as server computer 110 and/or user computer 105, in accordance with one or more embodiments of the present disclosure. Reference herein to a computer is to any device having a processor capable of executing logic or encoded instructions, which may be a server, a personal computer, a set-top box, a smart phone, a tablet, or a media device, among other such devices. As an example shown in FIG. 11, the internal architecture 1100 includes one or more processing units (also referred to herein as CPUs) 1112 connected to at least one computer bus 1102. Also connected to computer bus 1102 are: permanent storage media/media 1106, network interface 1114, memory 1104 such as Random Access Memory (RAM), run-time memory, Read Only Memory (ROM), etc., media disk drive interface 1108 that is a media drive interface for enabling reading and/or writing of removable media including floppy disks, CD-ROMs, DVDs, etc., display interface 1110 that is a display device interface for a monitor or other display device, keyboard interface 1116 that is a keyboard interface, pointing device interface 1118 that is a mouse or other pointing device interface, and various other interfaces not shown, such as parallel and serial port interfaces, Universal Serial Bus (USB) interfaces, etc.

Memory 1104 is coupled to computer bus 1102 to provide information stored in memory 1104 to CPU1112 during execution of software programs, such as an operating system, application programs, device drivers, and software modules including program code, and/or computer-executable process steps, incorporating functionality, such as one or more of the process flows described herein. First, CPU1112 loads computer-executable process steps from memory such as memory 1104, storage medium/media 1106, a removable media drive, and/or other memory drive. CPU1112 then executes the stored processing steps to perform the loaded computer-executable processing steps. In performing computer-executable process steps, CPU1112 may access stored data stored in a memory drive.

Non-transitory storage media/media 1106 is a computer-readable storage medium for storing software and data, such as an operating system and one or more application programs. Persistent storage media/media 1106 may also be used to store device drivers, web pages, content files, playlists and other files such as one or more digital camera drivers, monitor drivers, printer drivers, scanner drivers, or other device drivers. Persistent storage medium/media 1106 may also include: program modules and data files for implementing one or more embodiments of the disclosure.

For the purposes of this disclosure, a computer-readable medium stores computer data including computer program code executable by a computer in machine-readable form. By way of example, and not limitation, computer-readable media comprise: computer-readable storage media for the actual or fixed storage of data, or communication media for the transient analysis of signals containing code. Computer-readable storage media, as used herein, refers to physical or tangible memory (as opposed to signals), including, but not limited to, volatile and non-volatile, removable and fixed media implemented in any method or technology for the tangible storage of information such as computer-readable instructions, data structures, program modules or other data. Computer-readable storage media include, but are not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other physical or material media for tangibly storing desired information or data or instructions, which can be accessed by a computer or processor.

For purposes of this disclosure, a module may be a software, hardware, or firmware (or combination thereof) system, process, or function or component thereof that performs or facilitates the processes, features, and/or functions described herein (with or without human interaction or attachment). The module may include sub-modules. Software components of the module may be stored on a computer readable medium. The modules may be integrated in, or loaded and executed by, one or more servers. One or more modules may be grouped into engines or applications.

Those skilled in the art will appreciate that the methods and systems of the present disclosure may be implemented in many ways and, as such, are not limited to the foregoing exemplary embodiments and examples. In other words, functional elements being performed by single or multiple components, in various combinations of hardware and software or firmware, and individual functions, may be distributed among multiple software applications located on either the client or server side, or both. In this regard, many features of the different embodiments described herein may be combined in one or more embodiments, and alternative embodiments are possible that include fewer than or more than all of the features described herein. The functionality may also be distributed, in whole or in part, among multiple components, in manners now known or to become known. Thus, a wide variety of software/hardware/firmware combinations can implement the functions, features, interfaces and arrangements described herein. Moreover, it will be understood by those skilled in the art, now and in the future, that the scope of the present disclosure covers conventionally known manners for carrying out the described features, functions and structures, as well as those variations and modifications that may be made to the hardware, software or firmware components described herein.

While the systems and methods are described in terms of one or more embodiments, it is to be understood that the disclosure is not limited to the disclosed embodiments. The disclosure is intended to cover various modifications and similar arrangements included within the spirit and scope of the claims, the scope of which is to be accorded the broadest interpretation so as to encompass all such modifications and similar structures. This disclosure includes any and all embodiments of the following claims.

Claims (21)

1. A method, comprising:

receiving, by a computing device, from a user computer over a network, alphanumeric characters forming a portion of a search query submitted by a user in a search query entry area;

receiving, by the computing device, one or more search suggestions from a search suggestion module that are related to the partial search query;

prior to initiating the search query via user input, transmitting, by the computing device, the one or more search suggestions to the user computer for display by the user computer in a search suggestion region, the search suggestion region being displayed differently than a search results area;

transmitting, by the computing device, one of the one or more search suggestions to a rich content module;

the computing device receiving rich content from the rich content module related to the transmitted search suggestion; and

transmitting, by the computing device, the rich content to the user computer for display by the user computer in the search suggestion region prior to initiating the search query via user input.

2. The method of claim 1, wherein transmitting the search suggestion to a rich content module further comprises:

classifying, by the rich content module, the search suggestion into a category.

3. The method of claim 2, wherein categorizing the search suggestions further comprises:

classifying based on a classification technique selected from a set of classification technique types, wherein the classification technique types include a fixed priority order, a query classification confidence, a search session context using the user, and a search history profile using the user.

4. The method of claim 1, wherein the receiving rich content further comprises:

and erasing the network of the rich content.

5. The method of claim 4, wherein erasing the rich content network further comprises:

performing an erasure while the computing device and the user computer are in a non-communicating state.

6. The method of claim 1, wherein the receiving rich content further comprises:

the rich content is received from a database.

7. The method of claim 6, further comprising:

search engine query logs are mined by categorizing queries in the logs into one or more categories.

8. The method of claim 7, further comprising:

relationships are generated from a set of relationship types consisting of query-to-query relationships and query-to-search-result relationships.

9. The method of claim 7, further comprising:

social network feedback is used.

10. The method of claim 1, wherein the transmission of the rich content further comprises:

transmitting an advertisement as part of the rich content.

11. The method of claim 1, wherein the transmission of the one or more search suggestions further comprises:

transmitting a sponsored search suggestion as part of the one or more search suggestions.

12. The method of claim 1, further comprising:

updating the one or more search suggestions as additional alphanumeric characters are entered by the user in the search query entry area.

13. The method of claim 1, further comprising:

updating the rich content as additional alphanumeric characters are entered by a user in the search query entry area.

14. A computing device, comprising:

a network interface for receiving over a network alphanumeric characters forming part of a search query submitted by a user in a search query entry area from a user computer;

a search suggestion module to generate one or more search suggestions related to the partial search query, wherein the network interface transmits the one or more search suggestions to the user computer for display by the user computer in a search suggestion region, the search suggestion region being displayed differently than a search results region, prior to initiating the search query via user input;

a rich content module to receive one of the one or more search suggestions and generate rich content related to the transmitted search suggestion, wherein the network interface transmits the rich content to the user computer for display by the user computer in a search suggestion region prior to initiating the search query via user input.

15. The computing device of claim 14, wherein the rich content module categorizes the search suggestions into categories.

16. The computing device of claim 15, wherein the rich content module to categorize the search suggestion into categories further comprises:

the rich content module classifies based on a classification technique selected from a group of classification technique types, wherein the classification technique types include a fixed priority order, a query classification confidence, a search session context using the user, and a search history profile using the user.

17. The computing device of claim 14, wherein the rich content module erases a network of the rich content.

18. The computing device of claim 17, wherein the rich content module to erase the network of rich content further comprises:

the rich content module erases the network while the computing device is in a non-communication state with the user computer.

19. The computing device of claim 14, further comprising:

an advertisement server for transmitting advertisements as part of the rich content.

20. The computing device of claim 14, wherein the search suggestion module is further to transmit a sponsored search suggestion as part of the one or more search suggestions.

21. A computer readable storage medium tangibly storing thereon computer program instructions executable by a computer processor of a computing device, the computer program instructions comprising the steps of:

receiving, by the computing device, from a user computer over a network, alphanumeric characters forming a portion of a search query submitted by a user in a search query entry area;

receiving, by the computing device, one or more search suggestions from a search suggestion module that are related to the partial search query;

prior to initiating the search query via user input, transmitting, by the computing device, the one or more search suggestions to the user computer for display by the user computer in a search suggestion region, the search suggestion region being displayed differently than a search results area;

transmitting, by the computing device, one of the one or more search suggestions to a rich content module;

the computing device receiving rich content from the rich content module related to the transmitted search suggestion; and

transmitting, by the computing device, the rich content to the user computer for display by the user computer in a search suggestion region prior to initiating the search query via user input.