101 results about "Search ranking" patented technology

A method for presenting to an end-user the intermediate matching search results of a keyword search in an index list of information. The method comprising the steps of: coupling to a search engine a graphical user interface for accepting keyword search terms for searching the indexed list of information with the search engine; receiving one or more keyword search terms with one or more separation characters separating there between; performing a keyword search with the one or more keyword search terms received when a separation character is received; and presenting the number of documents matching the keyword search terms to the end-user presenting a graphical menu item on a display. A system and method of metadata search ranking is disclosed. The present invention utilizes a combination of popularity and / or relevancy to determine a search ranking for a given search result association.

A system and method of metadata search ranking is disclosed. The present invention utilizes a combination of popularity and / or relevancy to determine a search ranking for a given search result association. Given the exponential growth rate currently being experienced in the Internet community, the present invention provides one of the few methods by which searches of this vast distributed database can produce useful results ranked and sorted by usefulness to the searching web surfer. The present invention permits embodiments incorporating a Ranking System / Method (0100) further comprising a Session Manager (0101), Query Manager (0102), Popularity Sorter (0103), and Association (0104) functions. These components may be augmented in some preferred embodiments via the use of a Query Entry means (0155), Search Engine (0156); Data Repository (0157), Query Database (0158), and / or a Resource List (0159).

A preferred embodiment comprises the use of search rankings referring to a data object according to different sets of key words. So a search result according to a first set of key words might have a first ranking in a search result. The same data object including such as web pages and the like might have a second ranking if a second set of search words was used. The data object might appear in search results using a plurality of sets of key words and so when using the first set, also knowing the ranking from using the second set gives more information about the data object.

Systems and methods that improve search rankings for a search query by using data associated with queries related to the search query are described. In one aspect, a search query is received, a related query related to the search query is determined, an article (such as a web page) associated with the search query is determined, and a ranking score for the article based at least in part on data associated with the related query is determined. Several algorithms and types of data associated with related queries useful in carrying out such systems and methods are described.

Systems and methods that improve search rankings for a search query by using data associated with queries related to the search query are described. In one aspect, a search query is received, a population associated with the search query is determined, an article (such as a webpage) associated with the search query is determined, and a ranking score for the article based at least in part on data associated with the population is determined. Algorithms and types of data associated with a population useful in carrying out such systems and methods are described.

The present invention presents an apparatus and system for providing an ability to conduct a secondary search using results provided by a first search capability. This secondary search is integrated with the first search and functions as an added tool or accessory. The present invention allows for user control of search ranking, search viewing and search presentations thus affording more relevant information retrieval. Searchers can dynamically and interactively examine and manipulate the search results to improve relevance and quickly satisfy their search objectives.

The present invention presents an apparatus and system for providing an ability to conduct a secondary search using results provided by a first search capability. This secondary search is integrated with the first search and functions as an added tool or accessory. The present invention allows for user control of search ranking, search viewing and search presentations thus affording more relevant information retrieval. Searchers can dynamically and interactively examine and manipulate the search results to improve relevance and quickly satisfy their search objectives.

A computer based media, method and system for prioritizing search results for an individual, a group, a team, a division, an organization or some combination thereof.

A searcher can be configured to improve relevance ranking of search results through iterative weighting of search ranking results. A Search Auto Categorizer (SAC) operates on a base query to return a probabilistic distribution of leaf categories of a taxonomy in which relevant products may reside. A Search Logic Unit (SLU) can compute a relevance of any particular leaf category to the base query. The SLU can then determine an initial relevance of a particular product to the query based on the probabilistic distribution and the relevance of leaf category to query. The SLU weights the relevance of a product to the query to establish an updated probabilistic distribution. The SLU then repeats the relevance and weighting until convergence upon a relevance list.

An embodiment of the invention provides a searching-ranking model training method and device and a search processing method. The searching-ranking model training method includes: acquiring multiple groups of labeled sample data, wherein each group of the sample data includes search terms and multiple search result entries correspondingly labeled as positive examples or negative examples; generating Gated RNN (recurrent neural network) based input layer, word vector layer, hide layer and output layer of a searching-ranking model, and training the searching-ranking model to learn parameters of the same. By the searching-ranking model training method and device and the search processing method, accuracy of ranking scores of the search result entries acquired by calculating can be improved, and more accurate searching-ranking results are provided for users.

Methods and systems are provided for efficiently computing personalized rankings of web pages or other interconnected objects. The personalized rankings are produced by efficiently computing an approximation matrix to an ideal personalized page ranking matrix. The methods and systems provided herein can be used to produce search results with particular relevance to an individual searcher.

The present invention provides a search ranking method suitable for a file system, comprising: receiving a query; calculating final relevance scores of individual file items with respect to the query at least partially in accordance with energy scores of individual nodes on a current file system energy tree, and outputting a list of search results based on the final relevance scores; and updating the file system energy tree in response to an operation on the file system performed by a user, wherein the file system energy tree has a tree structure corresponding to that of the file system, and the individual nodes thereof respectively corresponds to the individual file items in the file system. The present invention also provides a corresponding file system search engine and computer program product. With the present invention, files and file folders that the user is interested in are usually arranged in relatively higher positions of the list of search results in file system search. Moreover, with the increase in the user's clicks on the file, the list of search results can be dynamically adapted to changes in the user's interest or preference.

A system and method for generating a search ranking score for a web page. The system comprises a training data processor effective to receive training data including at least a first page, a first label, a second page and a second label. The system further comprises a feature extraction processor connected to the training data processor, the feature extraction processor is effective to receive the first page, identify first features in the first page and calculate first values relating to the first features; the feature extraction processor is further effective to receive the second page and identify second features and calculate second values relating to the second features. A machine learning processor is connected to the feature extraction processor. The machine learning processor is effective to receive the first features, the first values, the first label, the second features, the second values, and the second label and generate a ranking function for a search engine based on the first features, the first values, the first label, the second features, the second values, and the second label. A receiving processor is connected to the machine learning processor. The receiving processor is effective to receive a web page. A ranking processor is connected to the receiving processor. The ranking processor is effective to apply the ranking function to the web page to generate a score.

A method and system are disclosed for optimizing search engine operations to increase the likelihood of attaining financial goals in a syndicated commerce environment. An SEO algorithm is implemented to determine keyword options for a predetermined product based upon the product's description, its web page content, and other related information. The SEO algorithm is then used to determine the product's associated search traffic and rank-per-keyword from various search engines. This information, in addition to sales conversion rate information, is then used to estimate the likelihood of monetization for one or more keyword. The product web page content is then automatically revised with an optimized combination of keywords. Once optimized, various search engines are automatically notified of the revisions to the web content pages to improve organic search rankings.

This is directed to a preview application for displaying several documents simultaneously in a single window, where the several documents are displayed as books. To view the pages of a document, the preview application can open the book and display the pages of the document (e.g., in a one or two-dimensional array). A user can also search for particular terms within the several documents. In response to a search, the preview application can filter the pages of the several documents and only display those pages that include the search terms. The displayed pages can be ordered in any suitable manner, including for example by search rank.

The invention discloses a device and a method for optimizing search ranking of frequently asked question and answer pairs, which is used for optimizing the ranking of search results searched by the frequently asked question and answer pairs. The method comprises the following steps: receiving a search query of a user, and obtaining multiple frequently asked question and answer pairs to be analyzed matched with the search query according to the search query of the user; according to a question and answer knowledge base including multiple question and answer knowledge records, obtaining associated degree of each frequently asked question and answer pair to be analyzed; according to the associated degrees of the frequently asked question and answer pairs to be analyzed, optimizing the search ranking of the frequently asked question and answer pairs to be analyzed matched. The device and the method can evaluate the associated degrees of the frequently asked question and answer pairs to be analyzed as the search results and optimize the ranking of the search results, and the ranking effect is better.

A system, method, and non-transitory computer-readable storage media includes a computer system having a server configured to generate labeled data on products to produce pairwise preferences, to combine the pairwise preferences, editorial ratings of the products, and inferred consumer relevances of the products to produce an ideal ranking for the products, to learn rerank function parameters based on the ideal ranking for the products, to output product rerank function parameters based on the learned rerank function parameters, to receive a product search query from a user device of a user, to get products that match the product search query, to rank the products based on the product rerank function parameters, and to output the ranked products as search results to the user device of the user.

A search system provides search results to searchers in response to search queries and the search results are ranked. The ranking is determined by an automated ranking process in combination with human editorial input. A search system might comprise a query server for receiving a current query, a corpus of documents to which the current query is applied, ranking data storage for storing information from an editorial session involving a human editor and a reviewed query at least similar to the current query, and a rank adjuster for generating a ranking of documents returned from the corpus responsive to the current query taking into account at least the information from the editorial session.

The embodiment of the invention provides a method and a device for training a ranking model. The method comprises the following steps: ranking search results corresponding to a user search request according to the ranking model to obtain a corresponding search ranking result; determining the search click rate corresponding to the ranking model according to a click feedback of a user aiming at the search ranking result; and carrying out updating on model parameters of the ranking model by a preset parameter updating algorithm according to the search click rate. According to the method and the device, the model parameters can be automatically adjusted to adapt to a click behavior of the user when behavioral preference of the changes; and compared with the condition that a data set needs to be reestablished in the prior art, the efficiency of training the model parameters can be improved.

The invention discloses a webpage text individualized searching method based on eyeball tracking, which comprises the following steps: 1) sample information of webpage text concerned time of a user is obtained by the use of an eyeball tracking device; 2) a user concerned time sample obtained is corrected; 3) an appropriate text similarity algorithm is dynamically selected by the application of a decision tree for an unknown webpage text; 4) the user concerned time of the unknown webpage text is predicted based on the text similarity; and 5) individualized webpage text searching results are generated by the use of the user concerned time and by the combination of traditional searching technology. The webpage text individualized searching method based on eyeball tracking effectively obtains individual reading interest of the user through the eyeball tracking device and combines the favorite of the user with the webpage text searching process, thus rendering the final webpage text searching ranking results to be closer to the ideal ranking expected by the user.

The embodiment of invention provides a lexical item weight labeling method and device, and relates to the technical field of internet search. The method includes the steps that all lexical items with weights to be determined are obtained; lexical item search weights of all the lexical items are calculated by combining search logs; according to occurrence frequencies of all the lexical items in a document set, reverse documents frequencies of all the lexical items are calculated; according to the lexical item search weights and reverse documents frequencies of all the lexical items and the, lexical item weights are calculated. The problem that in the method of using TF-IDF for calculating the lexical item weights in the internet search field, when a search task with a short text as the principal thing based on search words is implemented, important lexical items are marked with smaller weights is solved, the lexical item weights are calculated mainly based on the search logs, while connection between the lexical items and the search words is deepened, precision of correlation calculation between the lexical items and documents is improved in the search environment, and the search ranking quality is improved.

The invention discloses a data interaction method and device for a terminal device. The data interaction device comprises a memory module, an obtaining module, a matching module and a sending module, wherein the memory module is used for storing preset shopping recommended words; the obtaining module is used for obtaining a preset shopping recommended word relevant to the shopping behaviors of the terminal device; the matching module is used for matching the obtained shopping recommended word according to the same to obtain relevant commodity information of at least one commodity corresponding to the recommended word; the sending module is used for sending the obtained relevant commodity information of the at least one commodity through matching to the terminal device; the shopping recommended words are pre-obtained and stored from shopping session logs of electronic business websites, or the shopping recommended words are pre-obtained and stored from a commodity search ranking list of search websites. As the shopping recommended words are not required to be picked up by the aid of detailed and sufficient commodity information, the commodity recommended effect in the embodiment of the invention can be controlled conveniently; and moreover, through the personalized shopping recommendation based on the shopping recommended words, the complexity of a shopping recommendation system is simplified, and the real-time recommendation response speed is improved.

Disclosed is a technique for providing a linkage between applications, or other digital content, of an application store by assigning values to users of the digital content with respect to a particular user who is submitting a query for particular digital content. The technique involves receiving a query and identifying a subset of digital content based on the query and a word matching technique. For each identified digital content, users who have installed or downloaded the digital content may be determined. A reputation score, corresponding to a user's influence, and a trust score, corresponding to a degree of separation between the user who submitted the query and other users who have installed the digital content, may be computed for each of the users. A list of recommended applications may be generated based on the word matching technique, the reputation score, and the trust score.

The invention relates to computer technology and discloses a method and apparatus for training a multimedia file search ranking model, which is used for improving the sorting accuracy of search results. The method is, After identifying the keywords and the corresponding search results, calculating a ranking annotation function value of a search result corresponding to each keyword, and generates corresponding sample data, wherein, the sorting label function value is positively correlated with the clicked times of the multimedia file and the association degree of the subject type between the multimedia files, and the sample data whose sorting label function value meets the preset condition is screened out, the preset algorithm is used for model training, and the corresponding multimedia file search sorting model is generated. In this way, the sample data whose keywords are consistent with the search intention of the search results can be screened, the quality of the sample data is improved, the ranking accuracy of the multimedia file search ranking model obtained by training can be effectively improved, and the ranking optimization problem of the search results is solved.