In information retrieval research; Genetic Algorithms (GA) can be used to find global solutions in many difficult problems. This study used different similarity measures (Dice, Inner Product) in the VSM, for each similarity measure we compared ten different GA approaches based on different fitness functions, different mutations and different crossover strategies to find the best strategy and fi...

This paper presents the architecture of the Concept-based Vector Space Model Question Answering System (CBVSM-QAS) developed at the Nagaoka University of Technology (NUT) and used in the 4-th NTCIR workshop Question Answering Challenge (QAC) evaluation. The CBVSM-QAS runs on the factual question, which is, correspond to the subtask-1 in the NTCIR-4’s QAC. One major peculiarity of this system is...

Query expansion is an effective way to extend the coverage of retrieval to the related documents. Various approaches have been proposed and many of them are based o vector space model. The expansion process consists of simply adding expansion terms into the original vector. In this paper we argue that this simplistic expansion method can bias the focus of the original query, because the expande...

In this paper, we present an original framework to model frame semantic resources (namely, FrameNet) using minimal supervision. This framework can be leveraged both to expand an existing FrameNet with new knowledge, and to induce a FrameNet in a new language. Our hypothesis is that a frame semantic resource can be modeled and represented by a suitable semantic space model. The intuition is that...

Using i-vector space features has been shown to be very successful in speaker and language identification. In this paper, we evaluate using the i-vector framework for emotion recognition from speech. Instead of using standard i-vector features, we propose to use concatenated emotion specific i-vector features. For each emotion category, a GMM supervector is generated via adaptation of the neura...

In this paper we, in essence, point out that the methods used in the current vector based systems are in conflict with the premises of the vector space model. The considerations, naturally, lead to how things might have been done differently. More importantly, it is felt that this investigation will lead to a clearer understanding of the issues and problems in using the vector space model in in...

Music consumption habits as well as the Music market have changed dramatically due to the increasing popularity of digital audio and streaming services. Today, users are closer than ever to a vast number of songs, albums, artists and bands. However, the challenge remains in how to make sense of all the data available in the Music domain, and how current state of the art in Natural Language Proc...

WWW is a repository of large collection of information available in the form of unstructured documents. It is a challenging task to select the documents of interest from such a huge document pool. To fasten the process of document retrieval, text summarization technique is used. Ranking of documents is made based on the summary or the abstract provided by the authors of the document. But it is ...

By and large, three classic framework models have been used in the process of retrieving information: Boolean, Vector Space and Probabilistic. Boolean model is a light weight model which matches the query with precise semantics. Because of its boolean nature, results may be tides, missing partial matching, while on the contrary, vector space model, considering term-frequency, inverse document f...

In the software engineering world, creating and maintaining relationships between byproducts generated during the software lifecycle is crucial. A typical relation is the one that exists between an item in the requirements document and a block in the subsequent system design, i.e. class in the source code. In many software engineering projects, the requirement documentation is prepared in the l...