Semantic Technologies for Searching in e-Science Grids

Part of the Annals of Information Systems book series (AOIS, volume 11)


Searching is a key function in scientific cyber-infrastructures; there these systems need to implement superior meaning-based search functionalities powered by suitable semantic technologies. These required semantic technologies should enable computers to comprehend meaning of the objects being searched and user’s search intentions, compare these meanings, and discern which object may satisfy user’s need. We present a survey of meaning representation and comparison technologies, followed by a design of meaning representation and comparison technique which is coherent to the cognitive science and linguistics models. This proposed design addresses the key requirement of meaning compositionality which has not been addressed adequately and efficiently by existing research. We present an algebraic theory and techniques to represent hierarchically composed concepts as a tensor which is amenable to efficient semantic similarity computation. We delineate a data structure for the semantic descriptors/keys and an algorithm to generate them and describe an algorithm to compute the semantic similarity of two given descriptors (tensors). This meaning comparison technique discerns complex meaning while enabling search query relaxation and search key interchangeability. This is achieved without the need of a meaning knowledgebase (ontology).


Basis Vector Semantic Similarity Cosine Similarity Complex Concept Bloom Filter 


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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Computer ScienceTexas A&M UniversityTexasUSA

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