Abstract: Generating responses to input utilizing an ontology-crowd-relevance methodology is described. The techniques described herein access a plurality of data items and determine an ontology associated with the plurality of data items. The ontology includes one or more ontological elements. Furthermore, the techniques describe sending, to a plurality of devices, a request to generate response templates based on the one or more ontological elements and receiving, from the plurality of devices, the response templates directed to the one or more ontological elements.

Abstract: Generating responses to input utilizing an ontology-crowd-relevance methodology is described. The techniques described herein access a plurality of data items and determine an ontology associated with the plurality of data items. The ontology includes one or more ontological elements. Furthermore, the techniques describe sending, to a plurality of devices, a request to generate response templates based on the one or more ontological elements and receiving, from the plurality of devices, the response templates directed to the one or more ontological elements.

Abstract: A method, computing system, and one or more computer-readable storage media for clustering short answers to questions are provided herein. The method includes receiving, at a computing device, a number of short answers to a question from a number of remote computing devices. The method also includes automatically grouping the short answers into a number of clusters based on features corresponding to the short answers using a specified clustering technique.

Abstract: Systems and methods for providing organized content are described herein. In one example, a method includes identifying a spine document from a collection of documents, wherein the spine document comprises a plurality of sections. The method also includes splitting a related document into a plurality of subdocuments. In addition, the method includes mapping the subdocuments to corresponding sections of the spine document. Furthermore, the method includes displaying subdocuments based on a search of the collection of documents.

Abstract: Conceptually related term identification technique embodiments are presented that involve identifying in the results of a search query, terms that are conceptually related to the search query terms. In one general embodiment, this is accomplished by first inputting the terms employed in a search query and the results of the search. Word tokens found in the search query terms are then identified, as are potential phrases that can be made from the identified word tokens. Conceptually related words and phrases are then identified in the search query results. These words and phrases correspond to the previously identified word tokens and potential phrases. The search query results are presented to a user on a display device in such a manner as to visually distinguish the conceptually related words and phrases from other words and phrases in the search query results.

Abstract: Conceptually related term identification technique embodiments are presented that involve identifying in the results of a search query, terms that are conceptually related to the search query terms. In one general embodiment, this is accomplished by first inputting the terms employed in a search query and the results of the search. Word tokens found in the search query terms are then identified, as are potential phrases that can be made from the identified word tokens. Conceptually related words and phrases are then identified in the search query results. These words and phrases correspond to the previously identified word tokens and potential phrases. The search query results are presented to a user on a display device in such a manner as to visually distinguish the conceptually related words and phrases from other words and phrases in the search query results.

Abstract: Conceptually related term identification technique embodiments are presented that involve identifying in the results of a search query, terms that are conceptually related to the search query terms. In one general embodiment, this is accomplished by first inputting the terms employed in a search query and the results of the search. Word tokens found in the search query terms are then identified, as are potential phrases that can be made from the identified word tokens. Conceptually related words and phrases are then identified in the search query results. These words and phrases correspond to the previously identified word tokens and potential phrases. The search query results are presented to a user on a display device in such a manner as to visually distinguish the conceptually related words and phrases from other words and phrases in the search query results.

Abstract: The present invention is a method and system for identifying words, text fragments, or concepts of interest in a corpus of text. A graph is built which covers the corpus of text. The graph includes nodes and links, where nodes represent a word or a concept and links between the nodes represent directed relation names. A score is then computed for each node in the graph. Scores can also be computed for larger sub-graph portions of the graph (such as tuples) The scores are used to identify desired sub-graph portions of the graph, those sub-graph portions being referred to as graph fragments.

Abstract: The present invention can be used in a natural language processing system to determine a relationship (such as similarity in meaning) between two textual segments. The relationship can be identified or determined based on logical graphs generated from the textual segments. A relationship between first and second logical graphs is determined. This is accomplished regardless of whether there is an exact match between the first and second logical graphs. In one embodiment, the first graph represents an input textual discourse unit. The second graph, in one embodiment, represents information in a lexical knowledge base (LKB). The input graph can be matched against the second graph, if they have similar meaning, even if the two differ lexically or structurally.