48 research outputs found

    A Deleuzoguattarian Framework for Understanding Information Systems: the Case of Document Retrieval Systems

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    This paper aims to situate the study of information systems in a broader socio-political context. It is argued that information systems as any other social-technological system can serve as an agent of emancipation and change or as a site for reproduction of dominant power relations and subjugation. To illustrate this argument, concepts, such as, `deterritorialization\u27 and `reterritorialization\u27, borrowed from the philosophy of Deleuze & Guattari are adapted and applied to analyze the nature of interaction in document retrieval systems

    Lexical cohesion and term proximity in document ranking

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    Cataloged from PDF version of article.We demonstrate effective new methods of document ranking based on lexical cohesive relationships between query terms. The proposed methods rely solely on the lexical relationships between original query terms, and do not involve query expansion or relevance feedback. Two types of lexical cohesive relationship information between query terms are used in document ranking: short-distance collocation relationship between query terms, and long-distance relationship, determined by the collocation of query terms with other words. The methods are evaluated on TREC corpora, and show improvements over baseline systems. (C) 2008 Elsevier Ltd. All rights reserved

    Query expansion with terms selected using lexical cohesion analysis of documents

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    Cataloged from PDF version of article.We present new methods of query expansion using terms that form lexical cohesive links between the contexts of distinct query terms in documents (i.e., words surrounding the query terms in text). The link-forming terms (link-terms) and short snippets of text surrounding them are evaluated in both interactive and automatic query expansion (QE). We explore the effectiveness of snippets in providing context in interactive query expansion, compare query expansion from snippets vs. whole documents, and query expansion following snippet selection vs. full document relevance judgements. The evaluation, conducted on the HARD track data of TREC 2005, suggests that there are considerable advantages in using link-terms and their surrounding short text snippets in QE compared to terms selected from full-texts of documents. (C) 2006 Elsevier Ltd. All rights reserved

    Situating logic and information in information science

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    Information Science (IS) is commonly said to study collection, classification, storage, retrieval, and use of information. However, there is no consensus on what information is. This article examines some of the formal models of information and informational processes, namely, Situation Theory and Shannon's Information Theory, in terms of their suitability for providing a useful framework for studying information in IS. It is argued that formal models of information are concerned with mainly ontological aspects of information, whereas IS, because of its evaluative role with respect to semantic content, needs an epistemological conception of information. It is argued from this perspective that concepts of epistemological/aesthetic/ethical information are plausible, and that information science needs to rise to the challenge of studying many different conceptions of information embedded in different contexts. This goal requires exploration of a wide variety of tools from philosophy and logic. © 2009 ASIS&T

    Hybrid Synaptic Structure for Spiking Neural Network Realization

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    Neural networks and neuromorphic computing play pivotal roles in deep learning and machine vision. Due to their dissipative nature and inherent limitations, traditional semiconductor-based circuits face challenges in realizing ultra-fast and low-power neural networks. However, the spiking behavior characteristic of single flux quantum (SFQ) circuits positions them as promising candidates for spiking neural networks (SNNs). Our previous work showcased a JJ-Soma design capable of operating at tens of gigahertz while consuming only a fraction of the power compared to traditional circuits, as documented in [1]. This paper introduces a compact SFQ-based synapse design that applies positive and negative weighted inputs to the JJ-Soma. Using an RSFQ synapse empowers us to replicate the functionality of a biological neuron, a crucial step in realizing a complete SNN. The JJ-Synapse can operate at ultra-high frequencies, exhibits orders of magnitude lower power consumption than CMOS counterparts, and can be conveniently fabricated using commercial Nb processes. Furthermore, the network's flexibility enables modifications by incorporating cryo-CMOS circuits for weight value adjustments. In our endeavor, we have successfully designed, fabricated, and partially tested the JJ-Synapse within our cryocooler system. Integration with the JJ-Soma further facilitates the realization of a high-speed inference SNN.Comment: 7 pages, 10 figure

    Information arts and information science: Time to unite?

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    This article explicates the common ground between two currently independent fields of Inquiry, namely information arts and information science, and suggests a frame-work that could unite them as a single field of study. The article defines and clarifies the meaning of information art and presents an axiological framework that could be used to judge the value of works of information art. The axiological framework is applied to examples of works of information art to demonstrate its use. The article argues that both Information arts and Information science could be studied under a common framework; namely, the domain-analytic or sociocognitive approach. It also is argued that the unification of the two fields could help enhance the meaning and scope of both information science and information arts and therefore be beneficial to both fields

    Need for a systemic theory of classification in information science

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    In the article, the author aims to clarify some of the issues surrounding the discussion regarding the usefulness of a substantive classification theory in information science (IS) by means of a broad perspective. By utilizing a concrete example from the High Accuracy Retrieval from Documents (HARD) track of a Text REtrieval Conference (TREC), the author suggests that the "bag of words" approach to information retrieval (IR) and techniques such as relevance feedback have significant limitations in expressing and resolving complex user information needs. He argues that a comprehensive analysis of information needs involves explicating often-implicit assumptions made by the authors of scholarly documents, as well as everyday texts such as news articles. He also argues that progress in IS can be furthered by developing general theories that are applicable to multiple domains. The concrete example of application of the domain-analytic approach to subject analysis in IS to the aesthetic evaluation of works of information arts is used to support this argument

    On Document Relevance and Lexical Cohesion between Query Terms

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    Cataloged from PDF version of article.Lexical cohesion is a property of text, achieved through lexical-semantic relations between words in text. Most information retrieval systems make use of lexical relations in text only to a limited extent. In this paper we empirically investigate whether the degree of lexical cohesion between the contexts of query terms' occurrences in a document is related to its relevance to the query. Lexical cohesion between distinct query terms in a document is estimated on the basis of the lexical-semantic relations (repetition, synonymy, hyponymy and sibling) that exist between there collocates - words that co-occur with them in the same windows of text. Experiments suggest significant differences between the lexical cohesion in relevant and non-relevant document sets exist. A document ranking method based on lexical cohesion shows some performance improvements. (c) 2006 Elsevier Ltd. All rights reserved
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