Abstract: Methods, systems, computer-readable media, and apparatuses for providing search disambiguation using contextual information and domain ontologies are presented. In some embodiments, a computing device may receive a natural language input from a user. The computing device may identify a plurality of hypotheses for the natural language input. The computing device may map the plurality of hypotheses to one or more concepts of a plurality of concepts of an ontology by annotating the one or more concepts. The ontology may include the plurality of concepts respectively connected by a plurality of relations. The computing device may determine that there is an imperfect match between the annotated one or more concepts and annotations of answers. In response, the computing device may disambiguate the annotated one or more concepts using the ontology. The computing device may present output to the user based on the disambiguation.

Abstract: Aspects described herein provide solutions to problems posed by a user. Input that includes a specified subject may be received from a user. A specified descriptor for the specified subject may be obtained from a hierarchical taxonomy associated with the specified subject. An information repository may be searched based on the specific descriptor, and entries stored at the information repository that are associated with the specific descriptor may be indicated in a list of results. The specific descriptor may be iteratively generalized to obtain generalized descriptors, and the information repository may be searched based on the generalized descriptors. The generalized descriptors may also be specialized to obtain specialized descriptors, and the information repository may be searched based on the specialized descriptors. The list of results may include entries stored at the information repository that are respectively associated with the generalized descriptors and the specialized descriptors.

Abstract: Methods, devices, and computer program products for recognizing and responding to natural language input are described herein. Natural language input is received at a natural language input interface of a computing device and transformed into computer-usable text. A natural language input recognizer obtains evidence from one or more evidence source and generates an evidence graph based on the evidence obtained. Evidence may be obtained asynchronously, and the natural language input recognizer may update the evidence graph upon receipt of additional evidence. The natural language input recognizer generates a set of recognition hypotheses based on the evidence graph and selects one of the recognition hypotheses as a recognition result for the natural language input. Semantic models, evidence models, and response models may be employed to generate the evidence graph and respond to the recognition result selected for the natural language input.

Abstract: Aspects described herein provide solutions to problems posed by a user. Input that includes a specified subject may be received from a user. A specified descriptor for the specified subject may be obtained from a hierarchical taxonomy associated with the specified subject. An information repository may be searched based on the specific descriptor, and entries stored at the information repository that are associated with the specific descriptor may be indicated in a list of results. The specific descriptor may be iteratively generalized to obtain generalized descriptors, and the information repository may be searched based on the generalized descriptors. The generalized descriptors may also be specialized to obtain specialized descriptors, and the information repository may be searched based on the specialized descriptors. The list of results may include entries stored at the information repository that are respectively associated with the generalized descriptors and the specialized descriptors.

Abstract: Methods, devices, and computer program products for recognizing and responding to natural language input are described herein. Natural language input is received at a natural language input interface of a computing device and transformed into computer-usable text. A natural language input recognizer obtains evidence from one or more evidence source and generates an evidence graph based on the evidence obtained. Evidence may be obtained asynchronously, and the natural language input recognizer may update the evidence graph upon receipt of additional evidence. The natural language input recognizer generates a set of recognition hypotheses based on the evidence graph and selects one of the recognition hypotheses as a recognition result for the natural language input. Semantic models, evidence models, and response models may be employed to generate the evidence graph and respond to the recognition result selected for the natural language input.

Abstract: Methods, systems, computer-readable media, and apparatuses for providing search disambiguation using contextual information and domain ontologies are presented. In some embodiments, a computing device may receive a natural language input from a user. The computing device may identify a plurality of hypotheses for the natural language input. The computing device may map the plurality of hypotheses to one or more concepts of a plurality of concepts of an ontology by annotating the one or more concepts. The ontology may include the plurality of concepts respectively connected by a plurality of relations. The computing device may determine that there is an imperfect match between the annotated one or more concepts and annotations of answers. In response, the computing device may disambiguate the annotated one or more concepts using the ontology. The computing device may present output to the user based on the disambiguation.