An expert/expert-locating system based on automatic representation of semantic structure
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TL;DR
The expert/expert-locator (EEL) pairs requests for technical information with appropriate technical organizations in a large research and development company using a statistical matrix decomposition technique (singular value decomposition) to represent semantic similarity present in large text sources.
Abstract
The expert/expert-locator (EEL) pairs requests for technical information with appropriate technical organizations in a large research and development company. The system automatically constructs a semantic space of organizations and terms, using a statistical matrix decomposition technique (singular value decomposition) to represent semantic similarity present in large text sources. In EEL, organizations are characterized by their documents. Using these documents as input, the analysis simultaneously fits organizations and the terms they use into the same 100-dimensional space. Similarity among organizations is determined by their overall pattern of term usage. Users' requests are processed and also fit into the high-dimensional space. The similarities between the request all organizational objects in the space are computed, and the most similar organizations are returned to the user. It is shown that this technique is superior to keyword matching.>