Modern information retrieval systems use distributed and parallel algorithms to meet their operational requirements, and commonly operate on sparse vectors. But dimensionality-reducing techniques produce dense and relatively short feature vectors. Motivated by this relevance of dense vectors, we have parallelized the vector space model for dense matrices and vectors. Our algorithm uses a hybrid...

Traditional methods of summarization are not cost-effective and possible today. Extractive summarization is a process that helps to extract the most important sentences from a text automatically and generates a short informative summary. In this work, we propose an unsupervised method to summarize Persian texts. This method is a novel hybrid approach that clusters the concepts of the text using...

Instant intercommunion techniques such as Instant Messaging (IM) are widely popularized. Aiming at such kind of large scale masscommunication media, clustering on its text content is a practical method to analyze the characteristic of text content in instant messages, and find or track the social hot topics. However, key words in one instant message usually are few, even latent; moreover, sing...

Information retrieval is the area of finding particular web pages via a query to an internet search engine. Even though well sophisticated algorithms and data structures are used in traditional computer techniques to create indexes for efficiently organize and retrieve information systems, currently data mining techniques like clustering are used to enhance the efficiency of retrieval process. ...

We present the first fully unsupervised approach to metaphor interpretation, and a system that produces literal paraphrases for metaphorical expressions. Such a form of interpretation is directly transferable to other NLP applications that can benefit from a metaphor processing component. Our method is different from previous work in that it does not rely on any manually annotated data or lexic...

Under the Vector Space Model Tak W. Yan and Hector Garcia-Molina Department of Computer Science Stanford University Stanford, CA 94305 Abstract With the ever increasing volumes of electronic information generation, users of information systems are facing an information overload. It is desirable to support information ltering as a complement to traditional retrieval mechanism. The number of user...

Lyric-based song sentiment classification seeks to assign songs appropriate sentiment labels such as light-hearted and heavy-hearted. Four problems render vector space model (VSM)-based text classification approach ineffective: 1) Many words within song lyrics actually contribute little to sentiment; 2) Nouns and verbs used to express sentiment are ambiguous; 3) Negations and modifiers around t...

This paper proposes a patent map generation system using concept-based vector space model and presents evaluation results from the NTCIR-4 patent feasibility study (FS) task. The concept-base is a knowledge base of words, which expresses each word as an associated vector. The word vectors are computed based on word co-occurrence in a target document set, therefore, the word vectors reflect targ...

let $t$ be a bounded operator on the banach space $x$ and $ph$ be an analytic self-map of the unit disk $bbb{d}$‎. ‎we investigate some operator theoretic properties of‎ ‎bilateral composition operator $c_{ph‎, ‎t}‎: ‎f ri t circ f circ ph$ on the vector-valued hardy space $h^p(x)$ for $1 leq p leq‎ ‎+infty$.‎ ‎compactness and weak compactness of $c_{ph‎, ‎t}$ on $h^p(x)$‎ ‎are characterized an...