Abstract: A method, system and computer program product are disclosed for searching for data. In one embodiment, the invention provides a method comprising identifying a query and a search scope including a set of specified entities; and for each of these entities, estimating a number of documents that would be identified in a search through the entity to answer the query. On the basis of this estimating, a subset of the entities is formed. The query and this subset of entities are sent to a search engine to search the subset of entities to answer the query. In one embodiment, the estimating includes collecting statistical information from queries to build up a historical cache using heuristics or machine learning techniques, wherein the query includes a key word and a scope, and the historical cache contains a maximum number of returned results for an entity given the queries executed.

Abstract: Technical solutions are described for analyzing a natural language conversation-generating machine. The computer implemented method includes identifying, from a conversation log, a plurality of adjacency pairs. The method further includes determining, from the adjacency pairs, a number of adjacency pairs with outcome success indicators. The method further includes determining, from the adjacency pairs, a number of adjacency pairs with outcome failure indicators. The method further includes computing a mutual understanding score for the machine by computing a ratio of the number of adjacency pairs with outcome success indicators and the number of adjacency pairs with outcome failure indicators.

Abstract: A method, system and computer program product are disclosed for searching for data. In one embodiment, the invention provides a method comprising identifying a query and a search scope including a set of specified entities; and for each of these entities, estimating a number of documents that would be identified in a search through the entity to answer the query. On the basis of this estimating, a subset of the entities is formed. The query and this subset of entities are sent to a search engine to search the subset of entities to answer the query. In one embodiment, the estimating includes collecting statistical information from queries to build up a historical cache using heuristics or machine learning techniques, wherein the query includes a key word and a scope, and the historical cache contains a maximum number of returned results for an entity given the queries executed.

Abstract: A method, system and computer program product are disclosed for searching for data. In one embodiment, the invention provides a method comprising identifying a query and a search scope including a set of specified entities; and for each of these entities, estimating a number of documents that would be identified in a search through the entity to answer the query. On the basis of this estimating, a subset of the entities is formed. The query and this subset of entities are sent to a search engine to search the subset of entities to answer the query. In one embodiment, the estimating includes collecting statistical information from queries to build up a historical cache using heuristics or machine learning techniques, wherein the query includes a key word and a scope, and the historical cache contains a maximum number of returned results for an entity given the queries executed.

Abstract: A method, system, and computer program product are disclosed for merging search results. In one embodiment, the method comprises identifying a query, splitting the query into sub-queries, and calculating information content for each of the sub-queries. This method also comprises executing each of the sub-queries to obtain a plurality of search results, and combining the search results based on the information content calculated for the sub-queries. In an embodiment, the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; and the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters. In the embodiment the combining further includes merging the clusters based on the relevance scores computed for the clusters as well as the information content calculated for the sub-queries.

Abstract: A model is provided for managing resources in a programming environment. A first construct is triggered to update mutable entities in response to changes to related data associated with the mutable entities. In accordance with the updated mutable entities, at least one of a second construct and a third construct is triggered to respectively create a new mutable entity and update a data relationship.

Abstract: A mechanism is provided in a data processing system for automatically throttling the rate of service provided by a Web application programming interface (API) for a software service. A flow controller executing on the data processing system assigns a queue to each consumer of the software service. Responsive to receiving a current request for the software service from a given consumer of the software service, a flow controller executing on the data processing system adds the current request to a given queue assigned to the given consumer. The flow controller sends a next request from the given queue to the Web API based on a licensed rate of service of the given consumer.

Abstract: Technical solutions are described method for analyzing a natural language conversation-generating machine. An example computer implemented method includes determining, from a plurality of adjacency pairs in a conversation, a number of base pairs. The computer implemented method also includes determining, from the plurality of adjacency pairs, a number of expansion pairs. The computer implemented method also includes computing a efficiency score for the conversation by computing a ratio of the number of base pairs and the number of expansion pairs.

Abstract: Technical solutions are described for generating structured conversational data. An example method includes receiving an utterance that is part of a conversation and identifying the utterance as part of an adjacency pair. The adjacency pair includes two utterances, each produced by different speakers. The method also includes associating the utterance with a label from a predetermined set of labels based on the identifying of the adjacency pair.

Abstract: Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for implementing an extensible support system for multiple service offerings. For example, such a support system can be a business support system which may be employed in conjunction with a cloud computing environment.

Abstract: Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for ontology based resource provisioning and management for services. For example, such an ontology based approach can be utilized in conjunction with a business support system which may be employed in conjunction with a cloud computing environment.

Abstract: Technical solutions are described for generating structured conversational data. An example method includes receiving an utterance that is part of a conversation and identifying the utterance as part of an adjacency pair. The adjacency pair includes two utterances, each produced by different speakers. The method also includes associating the utterance with a label from a predetermined set of labels based on the identifying of the adjacency pair.

Abstract: Technical solutions are described for analyzing a natural language conversation-generating machine. The computer implemented method includes identifying, from a conversation log, a plurality of adjacency pairs. The method further includes determining, from the adjacency pairs, a number of adjacency pairs with outcome success indicators. The method further includes determining, from the adjacency pairs, a number of adjacency pairs with outcome failure indicators. The method further includes computing a mutual understanding score for the machine by computing a ratio of the number of adjacency pairs with outcome success indicators and the number of adjacency pairs with outcome failure indicators.

Abstract: Technical solutions are described method for analyzing a natural language conversation-generating machine. An example computer implemented method includes determining, from a plurality of adjacency pairs in a conversation, a number of base pairs. The computer implemented method also includes determining, from the plurality of adjacency pairs, a number of expansion pairs. The computer implemented method also includes computing a efficiency score for the conversation by computing a ratio of the number of base pairs and the number of expansion pairs.

Abstract: A mechanism is provided in a data processing system for automatically throttling the rate of service provided by a Web application programming interface (API) for a software service. A flow controller executing on the data processing system assigns a queue to each consumer of the software service. Responsive to receiving a current request for the software service from a given consumer of the software service, a flow controller executing on the data processing system adds the current request to a given queue assigned to the given consumer. The flow controller sends a next request from the given queue to the Web API based on a licensed rate of service of the given consumer.

Abstract: Technical solutions are described for generating structured conversational data. An example method includes receiving an utterance that is part of a conversation and identifying the utterance as part of an adjacency pair. The adjacency pair includes two utterances, each produced by different speakers. The method also includes associating the utterance with a label from a predetermined set of labels based on the identifying of the adjacency pair.

Abstract: Technical solutions are described for generating structured conversational data. An example method includes receiving an utterance that is part of a conversation and identifying the utterance as part of an adjacency pair. The adjacency pair includes two utterances, each produced by different speakers. The method also includes associating the utterance with a label from a predetermined set of labels based on the identifying of the adjacency pair.

Abstract: Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for implementing an extensible support system for multiple service offerings. For example, such a support system can be a business support system which may be employed in conjunction with a cloud computing environment.

Abstract: Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for implementing an extensible support system for multiple service offerings. For example, such a support system can be a business support system which may be employed in conjunction with a cloud computing environment.

Abstract: Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for ontology based resource provisioning and management for services. For example, such an ontology based approach can be utilized in conjunction with a business support system which may be employed in conjunction with a cloud computing environment.