Abstract: Elements in source data statements are matched to respective one or more entries in an ontology associated with a domain that had been selected for the source data statements. The source data statements had been received for a request. The ontology includes items and relationships that define the selected domain. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Abstract: A computer-implemented method includes: generating, by a computing device, a sample of a query, wherein the query maps to a predetermined categorization; processing the sample with a first natural language process, wherein the processing produces an output comprising a categorization of the sample; storing data regarding whether the categorization of the output matches the predetermined categorization; generating a report based on the stored data indicating a percentage of a plurality of samples of the query whose categorizations match the predetermined characterization; outputting the report; and receiving a second natural language process comprising updates to the first natural language process based on the report, wherein the updates increase the percentage of the plurality of samples that match the predetermined categorization when processed with the second natural language process relative to when the plurality of samples was processed with the first natural language process.

Abstract: A computer-implemented method includes: generating, by a computing device, a sample of a query, wherein the query maps to a predetermined categorization; processing the sample with a first natural language process, wherein the processing produces an output comprising a categorization of the sample; storing data regarding whether the categorization of the output matches the predetermined categorization; generating a report based on the stored data indicating a percentage of a plurality of samples of the query whose categorizations match the predetermined characterization; outputting the report; and receiving a second natural language process comprising updates to the first natural language process based on the report, wherein the updates increase the percentage of the plurality of samples that match the predetermined categorization when processed with the second natural language process relative to when the plurality of samples was processed with the first natural language process.

Abstract: A method for providing information to a user in response to a received user query. A natural language analysis generates substrings relevant to an input user query pertaining to a problem a user experiences with a product or service. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. Elements of a perfect or complete query are captured and include information pertaining to the user's problem. The input user query is refined based on the outputted terms and relationships between the terms. A search query is performed, based on the refined user query. The results of the search are provided to the user.

Abstract: A method for providing information to a user in response to a received user query. A natural language analysis generates substrings relevant to an input user query pertaining to a problem a user experiences with a product or service. An ontology analysis outputs: terms ontology matching the relevant generated substrings; and relationships between the terms. Elements of a perfect or complete query are captured and include information pertaining to the user's problem. The input user query is refined based on the outputted terms and relationships between the terms. A search query is performed, based on the refined user query. The results of the search are provided to the user.

Abstract: A system for implementing a method that provides information to a user in response to a received user query. A natural language analysis generates substrings relevant to the user query. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. A query analysis analyzes the user query regarding the outputted terms and relationships, including ascertaining whether the user query is more suitable for service than for an information search. If it is so ascertained, then service actions for the user to perform are identified to the user. If it is not so ascertained, then: the user query is refined based on the outputted terms and relationships; a search query is generated based on the refined user query, a search is initiated based on the search query, and results of the search are provided to the user.

Abstract: A system for implementing a method that provides information to a user in response to a received user query. A natural language analysis generates substrings relevant to the user query. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. A query analysis analyzes the user query regarding the outputted terms and relationships, including ascertaining whether the user query is more suitable for service than for an information search. If it is so ascertained, then service actions for the user to perform are identified to the user. If it is not so ascertained, then: the user query is refined based on the outputted terms and relationships; a search query is generated based on the refined user query, a search is initiated based on the search query, and results of the search are provided to the user.

Abstract: A method for providing information to a user in response to a received user query. A natural language analysis generates substrings relevant to the user query. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. A query analysis analyzes the user query regarding the outputted terms and relationships, including ascertaining whether the user query is more suitable for service than for an information search. If it is so ascertained, then service actions for the user to perform are identified to the user. If it is not so ascertained, then: the user query is refined based on the outputted terms and relationships; a search query is generated based on the refined user query, a search is initiated based on the search query, and results of the search are provided to the user.

Abstract: Elements in source data statements are matched to respective one or more entries in an ontology associated with a domain that had been selected for the source data statements. The source data statements had been received for a request. The ontology includes items and relationships that define the selected domain. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Abstract: Source data statements that had been received for the request are semantically analyzed, which includes matching elements in the received source data statements to respective one or more entries in an ontology associated with a domain that had been selected for the received source data statements. The ontology includes items and relationships that define the selected domain. Each element in the received source data statements is a word or a phrase. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Abstract: A natural language processing system and method resolves partial matches when a natural language input query does not fully specify an entity. The input query is tokenized into a set of query tokens, which are compared to contents of a searchable index, the contents representing entities, each of which is tokenized into a set of entity tokens associated with the tokenized entity. A plurality of partial match query tokens are identified from the set of query tokens, each partial match query token matching at least one entity token in the index. The entity(s) corresponding to each partial match query token are selected if a sequential break exists in the input query between the partial match query tokens and there is no intersection between the entity(s) corresponding to each partial match query token.

Abstract: A natural language processing system and method resolves partial matches when a natural language input query does not fully specify an entity. The input query is tokenized into a set of query tokens, which are compared to contents of a searchable index, the contents representing entities, each of which is tokenized into a set of entity tokens associated with the tokenized entity. A plurality of partial match query tokens are identified from the set of query tokens, each partial match query token matching at least one entity token in the index. The entity(s) corresponding to each partial match query token are selected if a sequential break exists in the input query between the partial match query tokens and there is no intersection between the entity(s) corresponding to each partial match query token.

Abstract: A natural language processing system and method resolves partial matches when a natural language input query does not fully specify an entity. The input query is tokenized into a set of query tokens, which are compared to contents of a searchable index, the contents representing entities, each of which is tokenized into a set of entity tokens associated with the tokenized entity. A plurality of partial match query tokens are identified from the set of query tokens, each partial match query token matching at least one entity token in the index. The entity(s) corresponding to each partial match query token are selected if a sequential break exists in the input query between the partial match query tokens and there is no intersection between the entity(s) corresponding to each partial match query token.

Abstract: Source data statements that had been received for the request are semantically analyzed, which includes matching elements in the received source data statements to respective one or more entries in an ontology associated with a domain that had been selected for the received source data statements. The ontology includes items and relationships that define the selected domain. Each element in the received source data statements is a word or a phrase. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Abstract: A method and system for semantic attribution of a request. Source data statements for the request are received. A selection of a domain for the received source data statements is received. The received source data statements are semantically analyzed, which includes matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain. The ontology includes items and relationships that define the selected domain. Each element in the received source data statements is a word or a phrase. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Abstract: A method, system, and computer program product for semantic attribution of a request. Source data statements for the request are received. A selection of a domain for the received source data statements is received. The received source data statements are semantically analyzed, which includes matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain. The ontology includes items and relationships that define the selected domain. Each element in the received source data statements is a word or a phrase. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations.

Abstract: A method and system for semantic attribution of a request. Source data statements for the request are received. A selection of a domain for the received source data statements is received. The received source data statements are semantically analyzed, which includes matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain. The ontology includes items and relationships that define the selected domain. Each element in the received source data statements is a word or a phrase. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Abstract: A natural language processing system and method resolves partial matches when a natural language input query does not fully specify an entity. The input query is tokenized into a set of query tokens, which are compared to contents of a searchable index, the contents representing entities, each of which is tokenized into a set of entity tokens associated with the tokenized entity. A plurality of partial match query tokens are identified from the set of query tokens, each partial match query token matching at least one entity token in the index. The entity(s) corresponding to each partial match query token are selected if a sequential break exists in the input query between the partial match query tokens and there is no intersection between the entity(s) corresponding to each partial match query token.

Abstract: A system for implementing a method that provides information to a user in response to a received user query. A natural language analysis generates substrings relevant to the user query. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. A query analysis analyzes the user query regarding the outputted terms and relationships, including ascertaining whether the user query is more suitable for service than for an information search. If it is so ascertained, then service actions for the user to perform are identified to the user. If it is not so ascertained, then: the user query is refined based on the outputted terms and relationships; a search query is generated based on the refined user query, a search is initiated based on the search query, and results of the search are provided to the user.

Abstract: A method for providing information to a user in response to a received user query. A natural language analysis generates substrings relevant to the user query. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. A query analysis analyzes the user query regarding the outputted terms and relationships, including ascertaining whether the user query is more suitable for service than for an information search. If it is so ascertained, then service actions for the user to perform are identified to the user. If it is not so ascertained, then: the user query is refined based on the outputted terms and relationships; a search query is generated based on the refined user query, a search is initiated based on the search query, and results of the search are provided to the user.