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 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: A method of integrated automatic support and assistance includes identifying a user and retrieving models representing the user's device, apparatus, service, or system, receiving a query from the user, as necessary refining the query, determining if the received query is a machine translatable query, restructuring machine translatable terms of the received query into semantic components based upon the retrieved models, determining a set of candidate knowledge bases both related to the semantic components, submitting the machine translatable query to each knowledge base of the set of candidate knowledge bases, receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting, formatting the set of responses, submitting the formatted set of responses to the user, determining if a response of the submitted formatted set of responses is accepted by the user, applying updated weights within the formatted set of responses, and storing the updated weights for future qu

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 method of integrated automatic support and assistance includes identifying a user and retrieving models representing the user's device, apparatus, service, or system, receiving a query from the user, as necessary refining the query, determining if the received query is a machine translatable query, restructuring machine translatable terms of the received query into semantic components based upon the retrieved models, determining a set of candidate knowledge bases both related to the semantic components, submitting the machine translatable query to each knowledge base of the set of candidate knowledge bases, receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting, formatting the set of responses, submitting the formatted set of responses to the user, determining if a response of the submitted formatted set of responses is accepted by the user, applying updated weights within the formatted set of responses, and storing the updated weights for future qu

Abstract: A method of integrated automatic support and assistance includes identifying a user and retrieving models representing the user's device, apparatus, service, or system, receiving a query from the user, as necessary refining the query, determining if the received query is a machine translatable query, restructuring machine translatable terms of the received query into semantic components based upon the retrieved models, determining a set of candidate knowledge bases both related to the semantic components, submitting the machine translatable query to each knowledge base of the set of candidate knowledge bases, receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting, formatting the set of responses, submitting the formatted set of responses to the user, determining if a response of the submitted formatted set of responses is accepted by the user, applying updated weights within the formatted set of responses, and storing the updated weights for future qu

Abstract: A method of integrated automatic support and assistance includes identifying a user and retrieving models representing the user's device, apparatus, service, or system, receiving a query from the user, as necessary refining the query, determining if the received query is a machine translatable query, restructuring machine translatable terms of the received query into semantic components based upon the retrieved models, determining a set of candidate knowledge bases both related to the semantic components, submitting the machine translatable query to each knowledge base of the set of candidate knowledge bases, receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting, formatting the set of responses, submitting the formatted set of responses to the user, determining if a response of the submitted formatted set of responses is accepted by the user, applying updated weights within the formatted set of responses, and storing the updated weights for future qu

Abstract: There is disclosed a system and method for interpreting and describing graphic images. In an embodiment, the method of inserting a description of an image into an audio recording includes: interpreting an image and producing a word description of the image including at least one image keyword; parsing an audio recording into a plurality of audio clips, and producing a transcription of each audio clip, each audio clip transcription including at least one audio keyword; calculating a similarity distance between the at least one image keyword and the at least one audio keyword of each audio clip; and selecting the audio clip transcription having a shortest similarity distance to the at least one image keyword as a location to insert the word description of the image. The word description of the image can then be appended to the selected audio clip to produce an augmented audio recording including the interpreted word description of the image.

Abstract: An expert system is used to recommend a customized solution for a customer. The expert system includes a set of scenarios each of which includes default facts and is associated with a detailed rule base that when applied in isolation to the default facts fully determines a prototype solution. A particular scenario is selected from the set based at least on user input. A customized solution is generated by applying the detailed rule base associated with the particular scenario to facts based at least on the user input and any default facts of the particular scenario that complement and do not conflict with the facts that are based at least on the user input. The customized solution is iteratively refined.

Abstract: There is disclosed a system and method for interpreting and describing graphic images. In an embodiment, the method of inserting a description of an image into an audio recording includes: interpreting an image and producing a word description of the image including at least one image keyword; parsing an audio recording into a plurality of audio clips, and producing a transcription of each audio clip, each audio clip transcription including at least one audio keyword; calculating a similarity distance between the at least one image keyword and the at least one audio keyword of each audio clip; and selecting the audio clip transcription having a shortest similarity distance to the at least one image keyword as a location to insert the word description of the image. The word description of the image can then be appended to the selected audio clip to produce an augmented audio recording including the interpreted word description of the image.

Abstract: A flavored and sweetened aqueous beverage which rapidly rehydrates dehydrated individuals, containing specified amounts of water, sodium chloride, citric acid and APM.