Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: generating domain language detection models respective to a plurality of domains. A query is mapped to a domain language detection model and intent of the query is determined by use of classification labels of the domain language detection model. Based on the classification labels that may be identified as the intent of the query, alternative queries are formed to be meaningful valid and are produced to a user.

Abstract: A method and system for improving a search query process is provided. The method includes analyzing via a natural language classifier (NLC) circuit of a hardware device, a partial search phase entered in a search field of a graphical user interface with respect to a search query for specified subject matter. A subject based intent classification associated with the search query is determined and compared to intent based data of an intent data repository. In response, an autocomplete phrase associated with the subject based intent classification and the partial search phrase is generated and presented to a user via the graphical user interface.

Abstract: An apparatus, method and associated system is described for the production of search results that are determined to be of interest to the user based on both the search phrase and the level of expertise of the user. Literature is analyzed from a plurality of different domains, and a database, map and/or lexicon is built that categorizes the literature by different levels of expertise. Each item of literature is assigned a particular level of expertise. At least one keyword in a user's search query is analyzed and compared with at least part of the database, and a user's level of expertise is based, at least in part, on the comparison. A set of search results is generated for the search query that is weighted, at least in part, based on a correlation between the user's level of expertise and the particular level of expertise assigned to each item of literature.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: generating domain language detection models respective to a plurality of domains. A query is mapped to a domain language detection model and intent of the query is determined by use of classification labels of the domain language detection model. Based on the classification labels that may be identified as the intent of the query, alternative queries are formed to be meaningful valid and are produced to a user.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: generating domain language detection models respective to a plurality of domains. A query is mapped to a domain language detection model and intent of the query is determined by use of classification labels of the domain language detection model. Based on the classification labels that may be identified as the intent of the query, alternative queries are formed to be meaningful valid and are produced to a user.

Abstract: A hierarchical data processor test system (and method) is usable to configure a hierarchical plurality of similarity operators and process predetermined input test data through a data processor under test (DPUT) to produce corresponding DPUT output data. The test system is further usable to process the DPUT output data and the predetermined output test data through at least some of the plurality of similarity operators in hierarchical order, determine a highest order similarity operator that indicates a match between the DPUT output data and the predetermined output test data, and compute a confidence score based on the highest order similarity operator that indicated the match. Based on the confidence score exceeding a threshold, the test system also may include activating the DPUT for use by non-test data.

Abstract: A method and system for improving a search query process is provided. The method includes analyzing via a natural language classifier (NLC) circuit of a hardware device, a partial search phase entered in a search field of a graphical user interface with respect to a search query for specified subject matter. A subject based intent classification associated with the search query is determined and compared to intent based data of an intent data repository. In response, an autocomplete phrase associated with the subject based intent classification and the partial search phrase is generated and presented to a user via the graphical user interface.

Abstract: A method and system for improving a search query process is provided. The method includes analyzing via a natural language classifier (NLC) circuit of a hardware device, a partial search phase entered in a search field of a graphical user interface with respect to a search query for specified subject matter. A subject based intent classification associated with the search query is determined and compared to intent based data of an intent data repository. In response, an autocomplete phrase associated with the subject based intent classification and the partial search phrase is generated and presented to a user via the graphical user interface.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: generating domain language detection models respective to a plurality of domains. A query is mapped to a domain language detection model and intent of the query is determined by use of classification labels of the domain language detection model. Based on the classification labels that may be identified as the intent of the query, alternative queries are formed to be meaningful valid and are produced to a user.

Abstract: An apparatus, method and associated system is described for the production of search results that are determined to be of interest to the user based on both the search phrase and the level of expertise of the user. Literature is analyzed from a plurality of different domains, and a database, map and/or lexicon is built that categorizes the literature by different levels of expertise. Each item of literature is assigned a particular level of expertise. At least one keyword in a user's search query is analyzed and compared with at least part of the database, and a user's level of expertise is based, at least in part, on the comparison. A set of search results is generated for the search query that is weighted, at least in part, based on a correlation between the user's level of expertise and the particular level of expertise assigned to each item of literature.

Abstract: A method and system for improving a search query process is provided. The method includes analyzing via a natural language classifier (NLC) circuit of a hardware device, a partial search phase entered in a search field of a graphical user interface with respect to a search query for specified subject matter. A subject based intent classification associated with the search query is determined and compared to intent based data of an intent data repository. In response, an autocomplete phrase associated with the subject based intent classification and the partial search phrase is generated and presented to a user via the graphical user interface.

Abstract: A hierarchical data processor test system (and method) is usable to configure a hierarchical plurality of similarity operators and process predetermined input test data through a data processor under test (DPUT) to produce corresponding DPUT output data. The test system is further usable to process the DPUT output data and the predetermined output test data through at least some of the plurality of similarity operators in hierarchical order, determine a highest order similarity operator that indicates a match between the DPUT output data and the predetermined output test data, and compute a confidence score based on the highest order similarity operator that indicated the match. Based on the confidence score exceeding a threshold, the test system also may include activating the DPUT for use by non-test data.