Techniques for use in identifying one of more concepts in a knowledge representation (KR). The techniques include obtaining user context information associated with a user, wherein the user context information comprises a plurality of words; Also included are semantic disambiguation techniques comprising obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first and second concept in a knowledge representation (KR) associated with a first meaning of the first portion. Semantic disambiguation techniques further include obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first concept and second concept in a knowledge representation (KR) using a measures of dominance and semantic coherence. Additionally, techniques are disclosed for calculating a measure of semantic coherence based on a graph of a knowledge representation (KR) and, an overlap of semantic context of a first concept and a second concept in the KR.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-27. (canceled) 28. A method comprising: obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and identifying a first concept associated with a meaning of the first portion from a first group of concepts in a knowledge representation (KR), wherein each concept in the first group of concepts is associated with a different meaning of the first portion, wherein the identifying is performed at least in part by using at least one processor, a measure of dominance of the first concept and a measure of semantic coherence between the first concept and a second concept in the KR, wherein the second concept is associated with a meaning of the second portion. 29. The method of claim 28, further comprising: calculating the measure of dominance of the first concept using a graph of the KR. 30. The method of claim 28, further comprising calculating the measure of semantic coherence between the first concept and the second concept by using a graph of the KR. 31. The method of claim 30, wherein calculating the measure of semantic coherence comprises: identifying a first semantic context of the first concept in the KR; identifying a second semantic context of the second concept in the KR; and calculating the measure of semantic coherence based on an amount of overlap between concepts in the first semantic context and concepts in the second semantic context. 32. The method of claim 30, further comprising: constructing a context intersection graph using the graph of the KR; calculating a score for each concept in the first group of concepts at least in part by using the context intersection graph; and identifying the first concept as a concept in the first group of concepts having the highest score. 33. The method of claim 28, wherein the knowledge representation is a semantic network represented by a data structure embodying a directed graph comprising a plurality of nodes and a plurality of edges, wherein each node is associated with a concept in the knowledge representation and an edge between two nodes represents a relationship between concepts associated with the two nodes. 34. The method of claim 28, wherein the user context information comprises at least one of a search query provided by the user, demographic information about the user, information from the user's browsing history, information typed by the user, and/or information highlighted by the user. 35. A system comprising: at least one processor configured to perform: obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and identifying a first concept associated with a meaning of the first portion from a first group of concepts in a knowledge representation (KR), wherein each concept in the first group of concepts is associated with a different meaning of the first portion, wherein the identifying is performed at least in part by using a measure of dominance of the first concept and a measure of semantic coherence between the first concept and a second concept in the KR, wherein the second concept is associated with a meaning of the second portion. 36. At least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising: obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and identifying a first concept associated with a meaning of the first portion from a first group of concepts in a knowledge representation (KR), wherein each concept in the first group of concepts is associated with a different meaning of the first portion, wherein the identifying is performed at least in part by using a measure of dominance of the first concept and a measure of semantic coherence between the first concept and a second concept in the KR, wherein the second concept is associated with a meaning of the second portion. 37. A method comprising: obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first concept in a knowledge representation (KR) associated with a first meaning of the first portion and a second concept in the KR associated with a second meaning of the first portion, wherein the disambiguating is performed at least in part by using at least one processor, a measure of dominance of the first concept, and a measure of semantic coherence between the first concept and a third concept associated with a meaning of the second portion. 38. A system comprising: at least one processor configured to perform: obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first concept in a knowledge representation (KR) associated with a first meaning of the first portion and a second concept in the KR associated with a second meaning of the first portion, wherein the disambiguating is performed at least in part by using a measure of dominance of the first concept and a measure of semantic coherence between the first concept and a third concept associated with a meaning of the second portion. 39. At least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising: obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first concept in a knowledge representation (KR) associated with a first meaning of the first portion and a second concept in the KR associated with a second meaning of the first portion, wherein the disambiguating is performed at least in part by using a measure of dominance of the first concept and a measure of semantic coherence between the first concept and a third concept associated with a meaning of the second portion. 40. A computer-implemented method, comprising: identifying, based on a graph of a knowledge representation (KR), a first semantic context of a first concept in the KR; identifying, based on the graph of the KR, a second semantic context of a second concept in the KR; and calculating, using at least one processor, a measure of semantic coherence between the first concept and the second concept based at least in part on an amount of overlap between the first semantic context and the second semantic context. 41. The method of claim 40, further comprising calculating the amount of overlap between the first semantic context and the second semantic context using Dice's coefficient. 42. The method of claim 40, further comprising calculating the amount of overlap based on labels of concepts in the first semantic context and labels of concepts in the second semantic context. 43. The method of claim 40, wherein identifying the first semantic context comprises identifying at least one direct attribute of the first concept in the KR. 44. The method of claim 40, wherein identifying the first semantic context comprises identifying at least one indirect attribute of the first concept in the KR. 45. The method of claim 40, wherein identifying the first semantic context comprises identifying at least one ancestor of the first concept in the KR. 46. The method of claim 40, wherein the first semantic context comprises at least one direct attribute of the first concept, at least one ancestor of the first concept, and at least one indirect attribute of the first concept. 47. The method of claim 40, wherein the first semantic context comprises concepts within a predetermined distance of the first concept on the graph of the KR. 48. The method of claim 40, wherein the knowledge representation is a semantic network represented by a data structure embodying a directed graph comprising a plurality of nodes and a plurality of edges, wherein each node is associated with a concept in the knowledge representation and an edge between two nodes represents a relationship between concepts associated with the two nodes. 49. The method of claim 37, wherein the user context information comprises at least one of a search query provided by the user, demographic information about the user, information from the user's browsing history, information typed by the user, and/or information highlighted by the user. 50. A system comprising: at least one processor configured to perform: identifying, based on a graph of a knowledge representation (KR), a first semantic context of a first concept in the KR; identifying, based on the graph of the KR, a second semantic context of a second concept in the KR; and calculating a measure of semantic coherence between the first concept and the second concept based at least in part on an amount of overlap between the first semantic context and the second semantic context. 51. At least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising: identifying, based on a graph of a knowledge representation (KR), a first semantic context of a first concept in the KR; identifying, based on the graph of the KR, a second semantic context of a second concept in the KR; and calculating a measure of semantic coherence between the first concept and the second concept based at least in part on an amount of overlap between the first semantic context and the second semantic context.