Semantic Search by Latent Ontological Features

Discovering Latent Concepts and Exploiting Ontological Features for Semantic Text Search

Named entities and WordNet words are important in defining the content of a text in which they occur. Named entities have ontological features, namely, their aliases, classes, and identifiers. WordNet words also have ontological features, namely, their synonyms, hypernyms, hyponyms, and senses. Those features of concepts may be hidden from their textual appearance. Besides, there are related co...

MOSSE: A Multi Ontological Semantic Search Engine

Search is one of the main motivations behind semantic web. A lot of proposals on semantic web search engines have been appeared in recent years but most of them are restricted to a limited context of web. Here we propose a scalable Multi Ontological Semantic Search Engine to conquer this problem. In addition some components of this architecture have been implemented and their results are reported.

Semantic Web Search Based on Ontological Conjunctive Queries

Many experts predict that the next huge step forward in Web information technology will be achieved by adding semantics to Web data, and will possibly consist of (some form of) the Semantic Web. In this paper, we present a novel approach to Semantic Web search, which allows for a semantic processing of Web search queries, and for evaluating complex Web search queries that involve reasoning over...

Building Semantic/Ontological Knowledge By Text Mining

Indexing by Latent Semantic Analysis

A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents ("semantic structure") in order to improve the detection of relevant documents on the basis of terms found in queries. The particular technique used is singular-value decomposition, in which a large term by document matri...