Abstract: A computer-implemented method according to one embodiment includes receiving a search query; determining a first set of categories associated with the search query, including performing a reverse lookup for the search query using a dynamic inference map in order to determine the first set of categories, where each category of the first set of categories includes one or more words that describe one or more aspects of the search query; determining a second set of categories associated with preliminary results of the search query; and filtering the preliminary results of the search query, including removing a subset of the preliminary results of the search query based on a comparison of the first set of categories to the second set of categories.

Abstract: A computer-implemented method according to one embodiment includes receiving a search query; determining a first set of categories associated with the search query, including performing a reverse lookup for the search query using a dynamic inference map in order to determine the first set of categories, where each category of the first set of categories includes one or more words that describe one or more aspects of the search query; determining a second set of categories associated with preliminary results of the search query; and filtering the preliminary results of the search query, including removing a subset of the preliminary results of the search query based on a comparison of the first set of categories to the second set of categories.

Abstract: A computer-implemented method according to one embodiment includes identifying a search query, determining a first set of categories associated with the search query, determining a second set of categories associated with preliminary results of the search query, and filtering the preliminary results of the search query based on an analysis utilizing the first set of categories and the second set of categories.

Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve receiving a plurality of documents having a set of subjects extracted through the use of latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.

Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve ingesting a plurality of documents; extracting a set of subjects from the plurality of documents using latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.

Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve receiving a plurality of documents having a set of subjects extracted through the use of latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.

Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve ingesting a plurality of documents; extracting a set of subjects from the plurality of documents using latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.

Abstract: A computer-implemented method according to one embodiment includes identifying a search query, determining a first set of categories associated with the search query, determining a second set of categories associated with preliminary results of the search query, and filtering the preliminary results of the search query based on an analysis utilizing the first set of categories and the second set of categories.

Abstract: A planar lightwave circuit has a waveguide having a bend and plurality of multiple trenches with parallel front and back interfaces. The trench and waveguide refractive indexes are different such that a refractive interface is defined between the waveguide and the trench. The trench may include a material of higher refractive index than the waveguide, such as silicon, or alternatively a material having a lower refractive index than the waveguide, such as an air void. The trench is disposed on the waveguide bend such that the front and back planar interfaces have an angle of incidence to a direction of the lightwave propagation from the waveguide. The invention also includes beamsplitters that include trenches that reflect a portion of a lightwave in a first direction and a portion of a lightwave in a second direction.