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Given a set of documents and an input query that is expressed using natural language, the problem of document search is retrieving all relevant documents ordered by the degree of relevance. Semantic document search fetches not only documents that contain words from the input query, but also documents that are semantically relevant. For example, the query "friendly pets" will consider documents...
Document clustering addresses the problem of identifying groups of similar documents without human supervision. Unlike most existing solutions that perform document clustering based on keywords matching, we propose an algorithm that considers the meaning of the terms in the documents. For example, a document that contains the words "dog" and "cat" multiple times may be placed in...
Given a set of documents and an input query that is expressed in a natural language, the problem of document search is retrieving the most relevant documents. Unlike most existing systems that perform document search based on keywords matching, we propose a search method that considers the meaning of the words in the query and the document. As a result, our algorithm can return documents that have...
The paper addresses the problem of modeling the relationship between phrases in English using a similarity graph. The mathematical model stores data about the strength of the relationship between phrases expressed as a decimal number. Both structured data from Wikipedia, such as that the Wikipedia page with title "Dog" belongs to the Wikipedia category "Domesticated animals", and...
Recently, several researchers have discovered the need for radios to use description techniques for the objects in the wireless realm. The concept of RF field-programmable analog array (FPAA) was also proposed recently and the lack of hardware abstractions was identified as a problem. We propose a hardware abstraction for RF FPAAs, which enables an open RF-digital interface. We advance the concept...
We propose a novel methodology for extracting semantic similarity knowledge from semi-structured sources, such as WordNet. Unlike existing approaches that only explore the structured information (e.g., the hypernym relationship in WordNet), we present a framework that allows us to utilize all available information, including natural language descriptions. Our approach constructs a semantic corpus...
Managing digital information is an integral part of our society. Efficient access to data is supported through the use of indices. Although indices can reduce the cost of answering queries, they have two significant drawbacks: they take additional storage space and their maintenance can become a bottleneck. We address these challenges by introducing search data structures that reduce the need for...
In this paper we explore the properties of description indices that store concept descriptions rather than plain data. Although these novel data structures are beneficial for efficiently answering semantic web queries, expressed in a language such as nRQL or SPARQL-DL, they take extra storage and their maintenance can become a performance bottleneck. In order to alleviate these shortcomings, we introduce...
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