Abstract: A computer-implemented technique is described herein for assisting an administrative user in generating negative feature information. The negative feature information, which includes a list of negative features (e.g., negative keywords), defines when queries submitted by end users are expressly disqualified as matching one or more parts of an identified web resource. The technique then automatically assesses the manner in which the negative feature information conflicts with matching between the queries submitted by end users and positive trigger information associated with the web resource, to provide conflict output information. The technique then modifies the negative feature information based on the conflict output information, e.g., by eliminating one or more negative keywords that contribute to conflicts.

Abstract: A computer-implemented technique is described herein for assisting an administrative user in generating negative feature information. The negative feature information, which includes a list of negative features (e.g., negative keywords), defines when queries submitted by end users are expressly disqualified as matching one or more parts of an identified web resource. The technique then automatically assesses the manner in which the negative feature information conflicts with matching between the queries submitted by end users and positive trigger information associated with the web resource, to provide conflict output information. The technique then modifies the negative feature information based on the conflict output information, e.g., by eliminating one or more negative keywords that contribute to conflicts.

Abstract: Systems, methods, and computer-readable storage media are provided for utilizing part-of-speech (POS) tagging of both the words included in a search query and the words included in potential search result documents to improve query alteration accuracy and search result ranking. Upon receiving a search query, POS tags are assigned to the words comprising the query to create query word-tag pairs. The query word-tag pairs are utilized to reformulate the query and are compared with document word-tag pairs included in a plurality of potential search result documents to determine a degree of similarity. The degree of similarity is utilized as an input in scoring and/or ranking the relevance of the potential search result documents with respect to one another.

Abstract: Described is a technology for identifying sample data items (e.g., documents corresponding to query-URL pairs) having the greatest likelihood of being mislabeled when previously judged, and selecting those data items for re-judging. In one aspect, lambda gradient scores (information associated with ranked sample data items that indicates a relative direction and how “strongly” to move each data item for lowering a ranking cost) are summed for pairs of sample data items to compute re-judgment scores for each of those sample data items. The re-judgment scores indicate a relative likelihood of mislabeling. Once the selected sample data items are re-judged, a new training set is available, whereby a new ranker may be trained.

Abstract: Methods, systems, and computer-readable media for a method of propagating signals across a web graph. A signal describes a document or otherwise provides useful information about a document in a web graph. A web graph is a collection of documents that are related to one another through links, such as hyperlinks. The signals are propagated in the sense that information from the related pages is associated with the target page even though the information may not be directly found in the target page. This information may then be used by a search engine to determine that a particular page is relevant to a search query.

Abstract: Systems, methods, and computer-readable storage media are provided for utilizing part-of-speech (POS) tagging of both the words included in a search query and the words included in potential search result documents to improve query alteration accuracy and search result ranking. Upon receiving a search query, POS tags are assigned to the words comprising the query to create query word-tag pairs. The query word-tag pairs are utilized to reformulate the query and are compared with document word-tag pairs included in a plurality of potential search result documents to determine a degree of similarity. The degree of similarity is utilized as an input in scoring and/or ranking the relevance of the potential search result documents with respect to one another.

Abstract: Architecture that generates signals/features that capture the match between intent of a query and category of documents. For example, for a query intent related to “autos”, documents that belong to categories related to “Autos” receive a higher score than documents of a “computers” category. The architecture can be applied to a search ecosystem where query intent classification and document category classifier are available, learns the mapping between query intent and document category, and introduces category-match features to a ranking algorithm, thereby improving search result relevance. The architecture learns the mapping between two existing and different taxonomies to create a category match signal from which the ranking algorithm can learn. Moreover, architecture adapts to a complex ecosystem where different taxonomies on the query side and document side exist through learning a mapping score between at least two taxonomies.

Abstract: Methods, systems, and computer-readable media for a method of propagating signals across a web graph. A signal describes a document or otherwise provides useful information about a document in a web graph. A web graph is a collection of documents that are related to one another through links, such as hyperlinks. The signals are propagated in the sense that information from the related pages is associated with the target page even though the information may not be directly found in the target page. This information may then be used by a search engine to determine that a particular page is relevant to a search query.

Abstract: Described is a technology for identifying sample data items (e.g., documents corresponding to query-URL pairs) having the greatest likelihood of being mislabeled when previously judged, and selecting those data items for re-judging. In one aspect, lambda gradient scores (information associated with ranked sample data items that indicates a relative direction and how “strongly” to move each data item for lowering a ranking cost) are summed for pairs of sample data items to compute re-judgment scores for each of those sample data items. The re-judgment scores indicate a relative likelihood of mislabeling. Once the selected sample data items are re-judged, a new training set is available, whereby a new ranker may be trained.

Abstract: Computerized methods and systems for generating a suggested query list with suggested search terms displayed as highlighted text utilizing a user-defined query are provided. Query search terms are received by a user-interface display. Upon inputting query search terms, the user-interface automatically generates a suggested query list. The suggested query list is associated with the query search term and the suggested query list is comprised of at least one suggested search term. A query suggestion architecture determines if the query search term and the suggested search term are a match, and if so, highlights the suggested search term that is not a match. The user interface displays the highlighted terms to assist in refining a search. The present invention further provides a stemming algorithm that extracts the root form of the query search term.

Abstract: Computerized methods and systems for generating a suggested query list with suggested search terms displayed as highlighted text utilizing a user-defined query are provided. Query search terms are received by a user-interface display. Upon inputting query search terms, the user-interface automatically generates a suggested query list. The suggested query list is associated with the query search term and the suggested query list is comprised of at least one suggested search term. A query suggestion architecture determines if the query search term and the suggested search term are a match, and if so, highlights the suggested search term that is not a match. The user interface displays the highlighted terms to assist in refining a search. The present invention further provides a stemming algorithm that extracts the root form of the query search term.