407results about How to "Improve the search experience" patented technology

The present invention relates to systems and methods that employ user models to personalize generalized queries and/or search results according to information that is relevant to respective user characteristics. A system is provided that facilitates generating personalized searches of information. The system includes a user model to determine characteristics of a user. The user model may be assembled automatically via an analysis of a user's content, activities, and overall context. A personalization component automatically modifies queries and/or search results in view of the user model in order to personalize information searches for the user. A user interface receives the queries and displays the search results from one or more local and/or remote search engines, wherein the interface can be adjusted in a range from more personalized searches to more generalized searches.

A video search system and method adapted to be queried by a user for accessing video data. The method comprising the steps of: providing an index containing a plurality of index data each indicative of one or more video data element accessible on a data network for defining a collection of the video data elements; receiving a user query from the user; matching the user query to one or more the index data defining a result set of index data; ranking the result set for defining a ranked result set of index data; generating a slicecast of video data elements indicative of the ranked result set; and presenting the slicecast to the user. A user interface adapted to present the slicecast of results preferably comprises a first current playlist video element area for playback of an extracted portion of a current playlist video item and a second list of playlist element area including a series of playlist videos for playback by a user.

Third party content providers can specify parameters for generating specialized search results in response to queries matching specific patterns. In this way, a generic search website can be enhanced to provide specialized search results to subscribed users. In one embodiment, these specialized results appear on a given user's result pages only when the user has subscribed to the enhancements from that particular content provider, so that users can tailor their search experience and see results that are more likely to be of interest to them. In other embodiments the specialized results are available to all users.

The invention provides an inquiring term rewriting method merging a term vector model and naive Bayes and relates to information processing technologies. The method includes the steps that word2vec is used for training the vector model, first N terms most similar to an inquiring term are calculated, and an initial relevant lexicon is formed; then, relevancy calculation and analysis are conducted, candidate terms for inquiring and rewriting the lexicon are filtered, and terms with high relevancy are reserved. The method can effectively improve the accuracy and recall degree of inquiring results and effectively solve the problem that search inquiring is in vain or few valid results are sent back.

The invention discloses a semantic search method based on multi-semantic analysis and personalized sequencing, and belongs to the field of information search. The semantic search method adopts the technical scheme comprising the following steps: firstly, by a crawler technology and other technologies, acquiring webpage documents from the Internet, classifying the webpage documents by using a support vector machine, establishing a word vector library by a multi-semantic analysis method, and writing multi-classification results into an index to form an index library; secondly, based on the word vector library, forming search keywords input by a user into a query vector, performing class matching query with the index library to obtain an initial sequencing result; and finally, according to personalized information and history access information of the user, optimizing the initial sequencing result, and returning the optimized result to the user. By the semantic search method based on the multi-semantic analysis and the personalized sequencing, the word vector library and the index library with rich semantemes are formed; and through the personalized information and the history access information, a search result can meet a search demand of the user better and search satisfaction of the user can be improved.

A method for enhancing web search experience of users. The method comprises selecting at least one resource from a plurality of resources to respond to an input query received from a user on a user device; sending the input query to the selected at least one resource; designating a unique display segment within a display area on the user device, wherein each display segment corresponds to each of the selected at least one resource; causing the selected at least one resource to respond to the input query within the corresponding unique display segment; and establishing a direct communication between each of the selected at least one resource and the user device for at least enabling, in response to the query, interaction of the selected at least one resource with the user within the unique display segment corresponding to the selected resource.

The invention discloses a hot-search word generation method and system, relating to the field of information processing. The invention is used for solving the problems that the prior art does not associate a search query Query hot-search word with a vertical portal webpage, and user search experience needs to be improved. The method comprises: storing a search query initiated by a user to a search engine; carrying out clustering operation to the search query to obtain a search query cluster; determining the hottest search query in the search query cluster; searching the above hottest search query in the vertical portal webpage to obtain webpage amount matched with the search query; taking the relevant search query cluster when the webpage amount is more than a first threshold value; and selecting the hottest search word from the search query cluster. The system comprises a search query storage module, a cluster module, a verification module, a page search module and a selection module. The invention verifies the search query hot-search word and the vertical portal webpage and can distinguish the search query hot-search word relevant to news or events.

A search interface and searching technology for interactive search refinement based on feature similarity (ISRFS), which provides an interactive search tool based on human associative and semantic knowledge. Given a query, the tool may retrieve the most suitable textual items in a repository of textual data that is categorized or/and partially tagged. In the user interface, an equalizer controller may be used to refine the search results, for example, based on manually or automatically extracted features and a graded semantic scale to adjust the weights of the various features. The technology may be applied to any data repository.

The invention discloses a method and a device for extracting searching value terms based on context search. The method comprises the following steps of: generating a candidate searching term set according to a selected content text; filtering broad terms from the generated candidate searching term set; performing topic relevance calculation and searching value calculation on the candidate searching term set from which the broad terms are filtered respectively; acquiring comprehensive weight measures of candidate searching terms according to a topic relevance calculation result and a searching value calculation result; and obtaining the searching value terms according to the comprehensive weight measures of the candidate searching terms. According to the method and the device, the searching requirements of a user in different places and different fields can be met, searching efficiency can be improved, and the searching experiences of the user can be improved.

The invention discloses a semantic search method and device based on a knowledge map, relating to the search engine field, which is used for satisfying the search requirements of a user at the semantic level, thereby providing an accurate and efficient search experience for the user. The method comprises the following steps of: obtaining search information; Carrying out semantic identification onthe search information according to the knowledge map to obtain the user intention; Reasoning and querying the first set of entities according to the user intention to obtain a second set of entities,wherein the second set of entities is a set of entities of high relevance to the user intention in the first set of entities; notifying The user of the second set of entities as a search result. Embodiments of the present application are applied to a semantic search based on a knowledge map.

The invention aims to provide a method and equipment for providing searching suggestions corresponding to a query sequence. The method comprises the following steps of: acquiring an optimal searching suggestion which is selected from one or more first searching suggestions through user equipment by a user, wherein the one or more first searching suggestions correspond to the query sequence input by the user; performing matching processing according to the optimal searching suggestion to obtain one or more second searching suggestions corresponding to the optimal searching suggestions; and providing at least one of the one or more second searching suggestions for the user equipment. The optimal searching suggestion which is selected from the first searching suggestions by the user is acquired, and the matching processing is performed according to the optimal searching suggestion to obtain the second searching suggestions which are provided for the user; and therefore, compared with theprior art, the invention provides richer searching suggestions for the user, provides a wider selection range for the user and improves the searching experiences of the user.

A document classification method and system based on document structure and style. The classification method and system categorizes document alphabetical words into complex and non-complex words, categorizes document linguistic sentences into subjective and non-subjective sentences and categorizes document images into descriptive and non-descriptive. The categorization is further used to calculate a complexity, subjectivity and descriptive-images classification of a document. This classification system can be used by a web search engine to filter, sort or tag a set of document references based on user selection.

The invention provides a search content providing method and a search engine. The search content providing method includes that the search engine acquires search data of a user; the search engine acquires a first associated word set and a second associated word set associated with preset keywords according to the search data; the search engine establishes association between first associated words in the first associated word set a nd second associated words in the second associated word set according to the search data and the preset keywords; when receiving a search request including the preset keywords, the search engine provides search content according to the association. By the search content providing method, the search content can be provided according to the association, more systematic and clearer search recommendations can be recommended to the user, convenience is brought to the user for accurately and quickly acquiring needed results, search requirements of the user can be met efficiently and accurately, and search experience of the user is good.

The present invention provides systems and methods that employ a statistical distributional analysis to improve content search engine search results. In particular, a substring and/or a string sequence distributional algorithm can be applied to a set of queries to generate a distributional characteristic (e.g., a profile) for the set of queries, wherein the set is selected from a plurality of queries stored on a query log. Typically, the queries are selected based on a substring of interest and/or an identification of a user initiating searches. The distributional characteristic can then be employed to determine a distributional similarity measure that can be utilized in connection with a search to facilitate search results via providing a mechanism to determine synonymous search terms, spelling corrections/variations, and facilitate collaborative filtering, for example. Thus, the present invention employs a novel technique that mines and employs previous queries to enhance the query search results.

The invention discloses a recommendation method for audio and video programs. The recommendation method includes collecting program information and user behavioral data of audio and video programs browsed by users; generating corresponding recommendation snapshots of the audio and video programs for the users according to the program information and the user behavioral data; and recommending audio and video programs to the users according to the recommendation snapshots of the audio and video programs. According to the technical scheme of the recommendation method for the audio and video programs, points of interest of the users can be accurately targeted, and experience of the users can be greatly improved, so that the recommendation snapshots obtained through intelligent analysis according to behaviors and tastes of the users are provided for each user, and searching experience of the users and browsing and watching rates of members are greatly improved.

The invention discloses a method for displaying commodity full results after commodity information input by a user. The method comprises the following steps that: inputting commodity information, wherein the commodity information comprises the picture information of a commodity or the combination of the picture information and the text information of the commodity; utilizing a pre-trained neural network to extract picture characteristics in the picture information of the commodity; obtaining commodity attributes corresponding to the picture characteristics, and/ or extracting keywords in the text information of the commodity, and obtaining the commodity attribute corresponding to the keywords; and matching the commodity attributes obtained in the commodity information with the commodity attributes of an established commodity mapping knowledge domain, and determining a target commodity with commodity attributes. The invention also discloses equipment which applies the method. By use ofthe method, image identification is combined with the commodity mapping knowledge domain corresponding to the image to realize a purpose that accurate and complete commodity full results are displayedafter the user inputs the commodity information, and convenient, efficient and accurate searching and shopping experience is brought to users.

The embodiment of the invention discloses a determination method and device for a recommended search keyword. The method comprises the steps that a target search term input by a user is obtained; whether the target search term is an entity is judged; if yes, an entity related to the target search term is determined according to a pre-established knowledge graph representing the relation between entities; and a first recommended search keyword corresponding to the target search term is determined according to the determined entity. By use of the embodiment, information relevance between the given recommended search keyword and a keyword input by the user is improved.

The invention discloses a search recommendation method. The search recommendation method comprises the following steps: receiving a picture input by a user; acquiring user identification; analyzing the picture to acquire search intention of the user; acquiring a corresponding recommendation model of the user according to the user identification; inquiring the recommendation model according to the search intention to acquire a recommendation result; providing the recommendation result in a search result web page. The method realizes the function of searching solid information and acquiring required information, enlarges search requirement range of the user, promotes search experience of the user, improves expansibility of a search engine, and adds the search function. The invention further discloses a search recommendation device.

The invention aims at providing a method and an equipment used for multi-media resource searching, wherein the multi-media searching equipment obtains the query sequence of the user; according to the query sequence, matching query is conducted in an index information bank so as to obtain a multi-media searching result corresponding to the query sequence; according to the multi-media searching result and a page corresponding to the multi-media searching result, a searching result corresponding to the query sequence is generated; and the searching result is provided for the user. The method and equipment realize that the user can obtain the multi-media resource information corresponding to the query sequence by directly browsing the searching result without clicking the searching result; the searching result clicking cost of the user, caused by querying the multi-media resource needed, can be reduced; the fast positioning of the multi-media resource searching result is realized; the searching efficiency and the searching accuracy of the user can be greatly improved, and the searching experience of the user is promoted.

The invention provides a search result sorting method and a search result sorting device. The method includes that a sorting device acquires search results corresponding to a query sequence input by a user; according to type information of the query sequence, a result sorting model corresponding to the query sequence is determined; according to the result sorting model, priority of the search results is determined; according to the priority, the search results are provided to the user. Compared with the prior art, the search result sorting method has the advantages that according to the type information of the query sequence, the result sorting model corresponding to the query sequence is determined, and the priority of the search results is further determined, so that the problems that a sorting result can possibly deviate from user expectation due to a sorting mode by simply using matched-degree information of a query request and the search results are solved; accuracy of the priority of the search results and efficiency for the information acquired by the user are improved, so that searching and using experience of the user is improved.

The invention discloses a hot word recommending method and device with combination of multiple data sources. The method comprises the following steps: screening hot data of the multiple data sources; selecting search logs of one or more users; intersecting the screened hot data and the search logs to generate a recommended hot word list; selecting a certain quantity of recommended hot words from the recommended hot word list for display. On the basis of the method and the device, on one hand, the recommended hot words are associated with historical search record of the user; on the other hand, the recommended hot words are associated with the search trend of the current society, the integrated recommended hot words are more accurate, effective and reliable, the search requirements of the user are met, and the search experience of the user is improved.

Embodiments of the invention provide a default search word recommendation method and apparatus. The method comprises the steps of obtaining a historical search word list of a current user; filtering the historical search word list according to a preset condition to generate a candidate search word set; querying characteristic information of candidate search words in the candidate search word set; and according to the characteristic information, recommending default search words according to a preset rule. According to the method and apparatus, the search words possibly interested by the user in a current state are mined and recommended by performing analytic processing on the historical search word list of the current user, so that the recommended search words can be closely related to a watch demand of the user, the recommendation effect is good, and the search experience of the user is improved.

The invention provides a searching method and device. One or more pieces of application demand information corresponding to a searching sequence of a user are confirmed according to the searching sequence; one or more integration searching results corresponding to the searching sequence are acquired based on the pieces of application demand information, wherein the integration searching results include a plurality of searching result subsets which correspond to the searching sequence and corresponding application demand information; the integration searching results are provided for the user. In this way, the searching method and device provide the integration searching results based on the searching sequence and the application demand information; compared with traditional searching results, the integration searching results are larger in information content; the searching results included in the searching result subsets can be defined by the searching result subsets in the integration searching results according to different dimensions so that more accurate information can be provided for the user and the user can search for required information more quickly.