126 results about "Re ranking" patented technology

A search engine for searching a corpus improves the relevancy of the results by refining a standard relevancy score based on the interconnectivity of the initially returned set of documents. The search engine obtains an initial set of relevant documents by matching a user's search terms to an index of a corpus. A re-ranking component in the search engine then refines the initially returned document rankings so that documents that are frequently cited in the initial set of relevant documents are preferred over documents that are less frequently cited within the initial set.

A method of retrieving documents using a search engine includes providing a reverse index including one or more keywords and a list of documents containing the one or more keywords, the reverse index further including a measure of confidence (MOC) value associated with the one or more keywords. One or more query terms are input into the search engine. The query terms are disambiguated and a MOC value is associated with each meaning of the disambiguated query term. A list of documents is retrieved containing the query terms wherein the documents are initially ranked based at least in part on the MOC values of the keywords and query terms. The list of documents may be re-ranked based at least in part on the semantic similarity of each document to the disambiguated query terms.

A search and recommendation system employs the preferences and profiles of individual users and groups within a community of users, as well as information derived from categorically organized content pointers, to augment electronic commerce related searches, re-rank search results, and provide recommendations for commerce related objects based on an initial subject-matter query and an interaction history of a user. The search and recommendation system operates in the context of a content pointer manager, which stores individual users' content pointers (some of which may be published or shared for group use) on a centralized content pointer database connected to a network. The shared content pointer manager is implemented as a distributed program, portions of which operate on users' terminals and other portions of which operate on the centralized content pointer database. A user's content pointers are organized in accordance with a local topical categorical hierarchy. The hierarchical organization is used to define a relevance context within which returned objects are evaluated and ordered.

Methods and systems are provided to present the search results in response to a search query that is submitted to a document retrieval system, such as a search engine. The search results are presented with a second-retrieval model that constructs multiple derived queries for the search query with a first small-document retrieval process, and then generates and outputs the results based on the retrieval of search results of at least part of the derived queries. One embodiment of the invention provides a method for grouping the search results, which presents ranked derived queries together with their search results to the user, in such a way that derived queries with higher ranks and top-ranked documents of each derived query are preferentially presented, and the grouped results are displayed and navigated in independent framed subareas of an output window. A further embodiment selects the search results from multiple result lists of the derived queries to form the final search results for the user query, wherein the merged results are re-ranked according to pre-determined criteria. The method can also be integrated with the local keyword associated clustering method by rank value adjustment, or result filtering or merging to achieve better technical effects.

In language evaluation systems, user expressions are often evaluated by speech recognizers and language parsers, and among several possible translations, a highest-probability translation is selected and added to a dialogue sequence. However, such systems may exhibit inadequacies by discarding alternative translations that may initially exhibit a lower probability, but that may have a higher probability when evaluated in the full context of the dialogue, including subsequent expressions. Presented herein are techniques for communicating with a user by formulating a dialogue hypothesis set identifying hypothesis probabilities for a set of dialogue hypotheses, using generative and/or discriminative models, and repeatedly re-ranks the dialogue hypotheses based on subsequent expressions. Additionally, knowledge sources may inform a model-based with a pre-knowledge fetch that facilitates pruning of the hypothesis search space at an early stage, thereby enhancing the accuracy of language parsing while also reducing the latency of the expression evaluation and economizing computing resources.

A portfolio selector technique is described for selecting publicly traded companies to include in a stock market portfolio. The technique is based on a technology score derived from the patent indicators of a set of technology companies with significant patent portfolios. Typical patent indicators may include citation indicators that measure the impact of patented technology on later technology, Technology Cycle Time that measures the speed of innovation of companies, and science linkage that measures leading edge tendencies of companies. Patent indicators measure the effect of quality technology on the company's future performance. The selector technique creates a scoring equation that weights each indicator such that the companies can be scored and ranked based on a combination of patent indicators. The score is then used to select the top ranked companies for inclusion in a stock portfolio. After a fixed period of time, as new patents are issued, the scores are recomputed such that the companies can be re-ranked and the portfolio adjusted to include new companies with higher scores and to eliminate companies in the current portfolio which have dropped in score. A portfolio of the top 10-25 companies using this method and a relatively simple scoring equation has been shown to greatly exceed the S&P 500 and other indexes in price gain over a ten year period.

A method and apparatus for dynamically modifying search results “on the fly” based on the behavior of the user currently conducting a search. In one embodiment, data regarding user behavior is gathered from virtually any activity, including clicks on links, dwell times, downloads, transactions and cursor movements. Subordinate keywords are generated to reflect the intent of the user as inferred from the user's behavior. Subordinate keywords, as opposed to traditional primary keywords, are keywords that are identified as important to the search, but are not necessarily essential for a matched document. They are automatically generated by the system from a variety of places, such as documents clicked on by the user as well as documents that are skipped. The system uses the subordinate keywords to dynamically re-rank matched documents and advertisements to best reflect the inferred intent of the user in order to continuously provide the most relevant results.

An Information highlighting facility assists the user in evaluating relevance of accessed documents to the user's information need. The accessed documents may, for example, be identified by a search engine in response to a user query. When accessing documents identified as relevant by a search engine from other networked computers, the facility provides information highlighting to assist the user in determining whether the document is relevant. A model of the user's interest, which may include an augmented set of search terms is used to take into account the general interest of the user as captured by an interest profile and context of use of the computer by the user, or a combination thereof. The model of the user's interest is applied to the document text as the document is accessed from its source. The highlighting of information about the document content may include highlighting of the terminology in the text, scrolling of the document to the relevant passages, identification of entity names and entity relations, creation of a document summary and a document thumbnail, etc. In addition, the model can be applied to a set of documents accessed by the user, e.g., to re-rank the top scoring documents from the result set provided to the user by a search engine or some other information providing services.

A technique for spectrum sensing management and control for a secondary communication system seeking to utilize another communication system's spectrum is provided (600). Sensor control data is sent from a base station to subscriber units (604). Sensing measurements are taken and sent back to the base station for ranking (608) as sensed feedback information. Comparisons of the sensed feedback information are made to each other and to thresholds aligned with the types of measurements taken (610). An initial ranked channel list is generated (612). Weighting of the initial ranking list and secondary ranking list is followed by re-ranking the channels according to the weighting into a final ranking list (612). The final ranking list is transmitted to the mobile units to enable operation within the other communication system's spectrum within interfering with that system (614). The weighting is based on the type of sensing measurement taken as opposed to the channel.

A system for and a method of using user-entered information to return more meaningful information in response to Internet search queries are disclosed. A method in accordance with the present invention comprises managing a database in response to multiple user inputs and displaying search results from the database in response to a search query. The search results include a results list and supplemental data related to the search query. Managing the database includes, among other things, re-ranking elements in the results list, storing information related to relevancies of elements in the results list, blocking a link in the results list, storing links to documents related to the search query, or any combination of these. The supplemental data include descriptions of or indices to one or more concepts related to the search query.

A method and apparatus using feedback obtained by user clicks and the position of the clicked images in the search result to determine user preferences for data that best satisfies particular queries. User click information is tracked to determine which images users click on for particular queries. This information is used to update and improve future query results. The described embodiment determines a user preference score for each image that is clicked for a given query. The placement of a clicked image in the search results is considered when computing the image/query score.

The present invention provides a method and system for re-ranking search results in a patent retrieval system where the query text is derived in whole or in part from a patent claim, which may be from an existing patent or a prospective claim. The re-ranking is based on several features of the candidate patent, such as the text similarity to the claim, international patent code or other classification or subject matter relatedness or overlap, and internal citation structure of the candidates. One alternative aspect provides a re-ranker that is trained on automatically generated training data, thus obviating the expensive and time-intensive step of expert annotation.

A search engine for databases, data streams, and other data sources allows user preferences as to the relative importance of search criteria to be used to rank the output of the search engine. A weighted preference generator generates weighted preference information including at least a plurality of weights corresponding to a plurality of search criteria. A weighted preference data search engine uses the weighted preference information to search a data source and to provide an ordered result list based upon the weighted preference information. A method for weighted preference data searching further includes allowing a user to re-rank the ordered result list and determine newly updated weighted preferences based on the re-ranking process. A plurality of weights signifying the relative importance of the search criteria may also be generated by the user inputting an ordered list. This ordered list may be a single alternative or a plurality of alternatives.

A method and a system for re-ranking an existing result set of documents. A user starts a search by entering search term(s). The search term(s) is (are) transferred to a search engine which generates a result set ranked by the search term(s). The search engine, in parallel, automatically retrieves context information from returned result set which is related to the original set of documents. The search engine presents the context information to the user and asks for a feedback. The user performs a weighting of the presented context information in a range from “important” to “non-important”. The result set is then re-ranked with the user-weighted context information to increase the “rank distance” of important and non important documents. The documents that are on top of the list (highest context-weighted ranking value) represent the desired information.

The invention is a method for retrieving answers to questions from an information retrieval system. The method involves automatically learning phrase features for classifying questions into different types, automatically generating candidate query transformations from a training set of question/answer pairs, and automatically evaluating the candidate transforms on information retrieval systems. At run time, questions are transformed into a set of queries, and re-ranking is performed on the documents retrieved.

Systems and methods for determining the authoritativeness of a document based on textual, non-topical cues. The authoritativeness of a document is determined by evaluating a set of document content features contained within each document to determine a set of document content feature values, processing the set of document content feature values through a trained document textual authority model, and determining a textual authoritativeness value and/or textual authority class for each document evaluated using the predictive models included in the trained document textual authority model. Estimates of a document's textual authoritativeness value and/or textual authority class can be used to re-rank documents previously retrieved by a search, to expand and improve document query searches, to provide a more complete and robust determination of a document's authoritativeness, and to improve the aggregation of rank-ordered lists with numerically-ordered lists.

An apparatus and method for quickly searching and ranking related documents in a database, and an interactive window that allows a user to dynamically reselect a priority of a score among a plurality of scores for re-ranking documents. In operation, the search engine 102 receives a query comprising a plurality of keywords from the user 100 via a user interface 101, performs a binary search on the sorted database 103 to quickly produce a list of files-of-interest. The ranking engine 104 uses the list of files-of-interest to search corresponding files in the list from the original database 105, score corresponding files to obtain the plurality of scores based on a plurality of paragraph scores for ranking files, where each paragraph score is calculated based on a number of matched query-keywords, frequency of occurrences and proximity distances between matched keywords within each paragraph.