Abstract: An expertise model based upon jargon usage is described. The expertise model is generated by an expertise model training system which includes a feature extractor to extract jargon-based features from a training text corpus. A model training component uses the features to generate the expertise model. The expertise model can be used for varied applications such as providing help resources in response to a user help inquiry or ranking or re-ranking query results.

Abstract: Refining a user query is disclosed. In one method, a query is received from a user, and then mapped to one or more search concepts. A list of search concepts associated with the query is then displayed. Alternatively or additionally, the search concepts associated with the query are used to provide a set of improved search results. In another method, a number of queries from a number of users are analyzed to identify two or more search concepts, and a popularity value is assigned to them based on the queries. Thus, the relative popularity of the respective search concepts can be determined. Alternatively or additionally, a preferred search query for the search concepts can be determined. The popularity and preferred queries can be used to allow automatic or user-initiated refinement.

Abstract: A spelling correction system and method for phrasal strings using a dictionary looping technique. The method of the present invention includes spelling correction of an input phrasal string by segmenting the string into a plurality of different segmentations, comparing each segmentation to dictionary entries using the dictionary looping technique, assigning a cost to each segmentation, and determining an output string by finding the segmentation having the lowest cost. The dictionary looping technique determines compares each segmentation to dictionary entries by performing a looping search through a phrasal dictionary data structure in a looping manner whereby a number of different searches are performed. Dictionary looping allows the dictionary to be compact because the dictionary need not include all potential combinations of all possible phrases that could be encountered. The present invention also includes a phrasal spelling correction system and a dynamic dictionary that uses the above-described method.

Abstract: Refining a user query is disclosed. In one method, a query is received from a user, and then mapped to one or more search concepts. A list of search concepts associated associated with the query is then displayed. Alternatively or additionally, the search concepts associated with the query are used to provide a set of improved search results. In another method, a number of queries from a number of users are analyzed to identify two or more search concepts, and a popularity value is assigned to them based on the queries. Thus, the relative popularity of the respective search concepts can be determined. Alternatively or additionally, a preferred search query for the search concepts can be determined. The popularity and preferred queries can be used to allow automatic or user-initiated refinement.

Abstract: A search and a browse on a single user query is performed. A refined query is selected from the results of the first user query. Thereafter, a list of concepts from a first directory associated with the refined query is obtained. The concepts are defined in a hierarchical relationship with concepts having broader scope being higher in the hierarchy and concepts having a narrower scope being lower in the hierarchy. Additionally, a list of web sites associated with the search concept is obtained from a second directory.

Abstract: A human assisted method of debugging training data used to train a machine learning classifier is provided. The method includes obtaining a classifier training data set. The training data set is then debugged using an integrated debugging tool configured to implement a debugging loop to obtain a debugged data set. The debugging tool can be configured to perform an estimation and simplification step to reduce data noise in the training data set prior to further analysis. The debugging tool also runs a panel of prediction-centric diagnostic metrics on the training data set, and provides the user prediction based listings of the results of the panel of prediction-centric diagnostic metrics.

Abstract: A search and a browse on a single user query is performed. A refined query is selected from the results of the first user query. Thereafter, a list of concepts from a first directory associated with the refined query is obtained. The concepts are defined in a hierarchical relationship with concepts having broader scope being higher in the hierarchy and concepts having a narrower scope being lower in the hierarchy. Additionally, a list of web sites associated with the search concept is obtained from a second directory.

Abstract: Candidate mappings are generated between two sets of short strings. A set of files related to the two sets of strings is chosen. Each string from the two sets of strings is searched for in the set of files. Any two strings that match the same file are presumed to be related, and are mapped together. These candidate mappings may then be checked by annotators/reviewers.

Abstract: A system that facilitates performance of a focused search over a collection of sites comprises a subweb that corresponds to a topic and/or user characteristic(s) that are of interest to the user. The subweb includes a plurality of domains and/or paths (e.g. sites) that are related to the topic and/or the user characteristic(s). Each of the sites within the subweb is assigned a weight that indicates relevance of the site to the desirable topic and/or user characteristic(s). A search engine employs the subweb to facilitate focusing a search over a collection of sites. The search engine receives a query, and utilizes the subweb to focus a search over the selection of sites corresponding to the topic and/or user characteristic(s) represented by the subweb. The results from the search are returned to the user based at least in part upon the relevance weights assigned to the sites within the subweb.

Abstract: The present invention relates to a system and methodology that applies automated learning procedures for determining document relevance and assisting information retrieval activities. A system is provided that facilitates a machine-learned approach to determine document relevance. The system includes a storage component that receives a set of human selected items to be employed as positive test cases of highly relevant documents. A training component trains at least one classifier with the human selected items as positive test cases and one or more other items as negative test cases in order to provide a query-independent model, wherein the other items can be selected by a statistical search, for example. Also, the trained classifier can be employed to aid an individual in identifying and selecting new positive cases or utilized to filter or re-rank results from a statistical-based search.

Abstract: Text classification has become an important aspect of information technology. Present text classification techniques range from simple text matching to more complex clustering methods. Clustering describes a process of discovering structure in a collection of characters. The invention automatically analyzes a text string and either updates an existing cluster or creates a new cluster. To that end, the invention may use a character n-gram matching process in addition to other heuristic-based clustering techniques. In the character n-gram matching process, each text string is first normalized using several heuristics. It is then divided into a set of overlapping character n-grams, where n is the number of adjacent characters. If the commonality between the text string and the existing cluster members satisfies a pre-defined threshold, the text string is added to the cluster. If, on the other hand, the commonality does not satisfy the pre-defined threshold, a new cluster may be created.

Abstract: A search and a browse on a single user query is performed. A refined query is selected from the results of the first user query. Thereafter, a list of concepts from a first directory associated with the refined query is obtained. The concepts are defined in a hierarchical relationship with concepts having broader scope being higher in the hierarchy and concepts having a narrower scope being lower in the hierarchy. Additionally, a list of web sites associated with the search concept is obtained from a second directory.

Abstract: Text classification has become an important aspect of information technology. Present text classification techniques range from simple text matching to more complex clustering methods. Clustering describes a process of discovering structure in a collection of characters. The invention automatically analyzes a text string and either updates an existing cluster or creates a new cluster. To that end, the invention may use a character n-gram matching process in addition to other heuristic-based clustering techniques. In the character n-gram matching process, each text string is first normalized using several heuristics. It is then divided into a set of overlapping character n-grams, where n is the number of adjacent characters. If the commonality between the text string and the existing cluster members satisfies a pre-defined threshold, the text string is added to the cluster. If, on the other hand, the commonality does not satisfy the pre-defined threshold, a new cluster may be created.

Abstract: A spelling correction system and method for phrasal strings using a dictionary looping technique. The method of the present invention includes spelling correction of an input phrasal string by segmenting the string into a plurality of different segmentations, comparing each segmentation to dictionary entries using the dictionary looping technique, assigning a cost to each segmentation, and determining an output string by finding the segmentation having the lowest cost. The dictionary looping technique determines compares each segmentation to dictionary entries by performing a looping search through a phrasal dictionary data structure in a looping manner whereby a number of different searches are performed. Dictionary looping allows the dictionary to be compact because the dictionary need not include all potential combinations of all possible phrases that could be encountered. The present invention also includes a phrasal spelling correction system and a dynamic dictionary that uses the above-described method.

Abstract: Refining a user query is disclosed. In one method, a query is received from a user, and then mapped to one or more search concepts. A list of search concepts associated with the query is then displayed. Alternatively or additionally, the search concepts associated with the query are used to provide a set of improved search results. In another method, a number of queries from a number of users are analyzed to identify two or more search concepts, and a popularity value is assigned to them based on the queries. Thus, the relative popularity of the respective search concepts can be determined. Alternatively or additionally, a preferred search query for the search concepts can be determined. The popularity and preferred queries can be used to allow automatic or user-initiated refinement.