Search (59 results, page 1 of 3)

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Abstract

While the Web has grown significantly in recent years, some portions of the Web remain largely underdeveloped, as shown in a lack of high-quality content and functionality. An example is the Arabic Web, in which a lack of well-structured Web directories limits users' ability to browse for Arabic resources. In this research, we proposed an approach to building Web directories for the underdeveloped Web and developed a proof-of-concept prototype called the Arabic Medical Web Directory (AMedDir) that supports browsing of over 5,000 Arabic medical Web sites and pages organized in a hierarchical structure. We conducted an experiment involving Arab participants and found that the AMedDir significantly outperformed two benchmark Arabic Web directories in terms of browsing effectiveness, efficiency, information quality, and user satisfaction. Participants expressed strong preference for the AMedDir and provided many positive comments. This research thus contributes to developing a useful Web directory for organizing the information in the Arabic medical domain and to a better understanding of how to support browsing on the underdeveloped Web.

Date

22. 3.2009 17:57:50

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.595-607

Theme

Information Gateway

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Abstract

With the growth of hypertext and multimedia applications that support and encourage browsing it is time to take a penetrating look at browsing behaviour. Several dimensions of browsing are exemined, to find out: first, what is browsing and what cognitive processes are associated with it: second, is there a browsing strategy, and if so, are there any differences between how subject-area experts and novices browse; and finally, how can this knowledge be applied to improve the design of hypertext systems. Two groups of students, subject-area experts and novices, were studied while browsing a Macintosh HyperCard application on the subject The Vietnam War. A protocol analysis technique was used to gather and analyze data. Components of the GOMS model were used to describe the goals, operators, methods, and selection rules observed: Three browsing strategies were identified: (1) search-oriented browse, scanning and and reviewing information relevant to a fixed task; (2) review-browse, scanning and reviewing intersting information in the presence of transient browse goals that represent changing tasks, and (3) scan-browse, scanning for interesting information (without review). Most subjects primarily used review-browse interspersed with search-oriented browse. Within this strategy, comparisons between subject-area experts and novices revealed differences in tactics: experts browsed in more depth, seldom used referential links, selected different kinds of topics, and viewed information differently thatn did novices. Based on these findings, suggestions are made to hypertext developers

Source

IEEE transactions on systems, man and cybernetics. 22(1992) no.5, S.865-884

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Abstract

It has become increasingly difficult to locate relevant information on the Web, even with the help of Web search engines. Two approaches to addressing the low precision and poor presentation of search results of current search tools are studied: meta-search and document categorization. Meta-search engines improve precision by selecting and integrating search results from generic or domain-specific Web search engines or other resources. Document categorization promises better organization and presentation of retrieved results. This article introduces MetaSpider, a meta-search engine that has real-time indexing and categorizing functions. We report in this paper the major components of MetaSpider and discuss related technical approaches. Initial results of a user evaluation study comparing Meta-Spider, NorthernLight, and MetaCrawler in terms of clustering performance and of time and effort expended show that MetaSpider performed best in precision rate, but disclose no statistically significant differences in recall rate and time requirements. Our experimental study also reveals that MetaSpider exhibited a higher level of automation than the other two systems and facilitated efficient searching by providing the user with an organized, comprehensive view of the retrieved documents.

Source

Journal of the American Society for Information Science and technology. 52(2001) no.13, S.1134-1147

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Abstract

As the Internet becomes ubiquitous, it has advanced to more closely represent aspects of the real world. Due to this trend, researchers in various disciplines have become interested in studying relationships between real-world phenomena and their virtual representations. One such area of emerging research seeks to study relationships between real-world and virtual activism of social movement organization (SMOs). In particular, SMOs holding extreme social perspectives are often studied due to their tendency to have robust virtual presences to circumvent real-world social barriers preventing information dissemination. However, many previous studies have been limited in scope because they utilize manual data-collection and analysis methods. They also often have failed to consider the real-world aspects of groups that partake in virtual activism. We utilize automated data-collection and analysis methods to identify significant relationships between aspects of SMO virtual communities and their respective real-world locations and ideological perspectives. Our results also demonstrate that the interconnectedness of SMO virtual communities is affected specifically by aspects of the real world. These observations provide insight into the behaviors of SMOs within virtual environments, suggesting that the virtual communities of SMOs are strongly affected by aspects of the real world.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.11, S.2210-2222

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Abstract

The Internet provides an exceptional testbed for developing algorithms that can improve bowsing and searching large information spaces. Browsing and searching tasks are susceptible to problems of information overload and vocabulary differences. Much of the current research is aimed at the development and refinement of algorithms to improve browsing and searching by addressing these problems. Our research was focused on discovering whether two of the algorithms our research group has developed, a Kohonen algorithm category map for browsing, and an automatically generated concept space algorithm for searching, can help improve browsing and / or searching the Internet. Our results indicate that a Kohonen self-organizing map (SOM)-based algorithm can successfully categorize a large and eclectic Internet information space (the Entertainment subcategory of Yahoo!) into manageable sub-spaces that users can successfully navigate to locate a homepage of interest to them. The SOM algorithm worked best with browsing tasks that were very broad, and in which subjects skipped around between categories. Subjects especially liked the visual and graphical aspects of the map. Subjects who tried to do a directed search, and those that wanted to use the more familiar mental models (alphabetic or hierarchical organization) for browsing, found that the work did not work well. The results from the concept space experiment were especially encouraging. There were no significant differences among the precision measures for the set of documents identified by subject-suggested terms, thesaurus-suggested terms, and the combination of subject- and thesaurus-suggested terms. The recall measures indicated that the combination of subject- and thesaurs-suggested terms exhibited significantly better recall than subject-suggested terms alone. Furthermore, analysis of the homepages indicated that there was limited overlap between the homepages retrieved by the subject-suggested and thesaurus-suggested terms. Since the retrieval homepages for the most part were different, this suggests that a user can enhance a keyword-based search by using an automatically generated concept space. Subejcts especially liked the level of control that they could exert over the search, and the fact that the terms suggested by the thesaurus were 'real' (i.e., orininating in the homepages) and therefore guaranteed to have retrieval success

Source

Journal of the American Society for Information Science. 49(1998) no.7, S.582-603

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Date

22. 7.2006 14:26:01

Source

Journal of the American Society for Information Science and Technology. 56(2005) no.5, S.457-468

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Date

22. 7.2006 16:14:37

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.378-393

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Date

22. 3.2009 18:50:30

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.655-665

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Abstract

Findings The findings of this research suggest that individual learning and development are deemed to be the fundamental feature for professional success and survival in the continuously changing environment of the SW industry today. However, individual learning was described by the participants as much more than a mere individual process. It involves a collective and participatory effort within the organization and the sector as a whole, and a KS process that transcends organizational, cultural and national borders. Individuals in particular are mostly motivated by the pressing need to face and adapt to the dynamic and changeable environments of today's digital society that is led by the sector. Software practitioners are continuously in need of learning, refreshing and accumulating tacit knowledge, partly because it is required by their companies, but also due to a sound awareness of continuous technical and technological changes that seem only to increase with the advances of information technology. This led to a clear theoretical understanding that the continuous change that faces the sector has led to individual acquisition of culture and somatic knowledge that in turn lay the foundation for not only the awareness of the need for continuous individual professional development but also for the creation of habitus related to KS and continuous learning. Originality/value The study reported in this paper shows that there is a theoretical link between the existence of conducive organizational and sector-wide somatic and cultural knowledge, and the success of KS practices that lead to individual learning and development. Therefore, the theory proposed suggests that somatic and cultural knowledge are crucial drivers for the creation of habitus of individual tacit knowledge acquisition. The paper further proposes a habitus-driven individual development (HDID) Theoretical Model that can be of use to both academics and practitioners interested in fostering and developing processes of KS and individual development in knowledge-intensive organizations.

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Abstract

Information retrieval using probabilistic techniques has attracted significant attention on the part of researchers in information and computer science over the past few decades. In the 1980s, knowledge-based techniques also made an impressive contribution to 'intelligent' information retrieval and indexing. More recently, information science researchers have tfurned to other newer inductive learning techniques including symbolic learning, genetic algorithms, and simulated annealing. These newer techniques, which are grounded in diverse paradigms, have provided great opportunities for researchers to enhance the information processing and retrieval capabilities of current information systems. In this article, we first provide an overview of these newer techniques and their use in information retrieval research. In order to femiliarize readers with the techniques, we present 3 promising methods: the symbolic ID3 algorithm, evolution-based genetic algorithms, and simulated annealing. We discuss their knowledge representations and algorithms in the unique context of information retrieval

Source

Journal of the American Society for Information Science. 49(1998) no.8, S.693-705

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Abstract

In this era of the Internet and distributed, multimedia computing, new and emerging classes of information systems applications have swept into the lives of office workers and people in general. From digital libraries, multimedia systems, geographic information systems, and collaborative computing to electronic commerce, virtual reality, and electronic video arts and games, these applications have created tremendous opportunities for information and computer science researchers and practitioners. As applications become more pervasive, pressing, and diverse, several well-known information retrieval (IR) problems have become even more urgent. Information overload, a result of the ease of information creation and transmission via the Internet and WWW, has become more troublesome (e.g., even stockbrokers and elementary school students, heavily exposed to various WWW search engines, are versed in such IR terminology as recall and precision). Significant variations in database formats and structures, the richness of information media (text, audio, and video), and an abundance of multilingual information content also have created severe information interoperability problems -- structural interoperability, media interoperability, and multilingual interoperability.

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Abstract

Attempts to identify the nature and causes of information management indeterminism in an online research environment and proposes solutions for alleviating this indeterminism. Conducts two empirical studies of information management activities. The first identified the types and nature of information management indeterminism by evaluating archived text. The second focused on four sources of indeterminism: subject area knowledge, classification knowledge, system knowledge, and collaboration knowledge. Proposes a knowledge based design for alleviating indeterminism, which contains a system generated thesaurus and an inferencing engine

Source

Information processing and management. 30(1994) no.4, S.557-577

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Abstract

In the 1980s, knowledge-based techniques also made an impressive contribution to 'intelligent' information retrieval and indexing. More recently, researchers have turned to newer artificial intelligence based inductive learning techniques including neural networks, symbolic learning, and genetic algorithms grounded on diverse paradigms. These have provided great opportunities to enhance the capabilities of current information storage and retrieval systems. Provides an overview of these techniques and presents 3 popular methods: the connectionist Hopfield network; the symbolic ID3/ID5R; and evaluation based genetic algorithms in the context of information retrieval. The techniques are promising in their ability to analyze user queries, identify users' information needs, and suggest alternatives for search and can greatly complement the prevailing full text, keyword based, probabilistic, and knowledge based techniques

Source

Journal of the American Society for Information Science. 46(1995) no.3, S.194-216

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Abstract

To make good decisions, businesses try to gather good intelligence information. Yet managing and processing a large amount of unstructured information and data stand in the way of greater business knowledge. An effective business intelligence tool must be able to access quality information from a variety of sources in a variety of forms, and it must support people as they search for and analyze that information. The EBizPort system was designed to address information needs for the business/IT community. EBizPort's collection-building process is designed to acquire credible, timely, and relevant information. The user interface provides access to collected and metasearched resources using innovative tools for summarization, categorization, and visualization. The effectiveness, efficiency, usability, and information quality of the EBizPort system were measured. EBizPort significantly outperformed Brint, a business search portal, in search effectiveness, information quality, user satisfaction, and usability. Users particularly liked EBizPort's clean and user-friendly interface. Results from our evaluation study suggest that the visualization function added value to the search and analysis process, that the generalizable collection-building technique can be useful for domain-specific information searching an the Web, and that the search interface was important for Web search and browse support.

Source

Journal of the American Society for Information Science and Technology. 55(2004) no.10, S.873-891

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Abstract

Advanced technology has resulted in the generation of about one million terabytes of information every year. Ninety-reine percent of this is available in digital format (Keim, 2001). More information will be generated in the next three years than was created during all of previous human history (Keim, 2001). Collecting information is no longer a problem, but extracting value from information collections has become progressively more difficult. Various search engines have been developed to make it easier to locate information of interest, but these work well only for a person who has a specific goal and who understands what and how information is stored. This usually is not the Gase. Visualization was commonly thought of in terms of representing human mental processes (MacEachren, 1991; Miller, 1984). The concept is now associated with the amplification of these mental processes (Card, Mackinlay, & Shneiderman, 1999). Human eyes can process visual cues rapidly, whereas advanced information analysis techniques transform the computer into a powerful means of managing digitized information. Visualization offers a link between these two potent systems, the human eye and the computer (Gershon, Eick, & Card, 1998), helping to identify patterns and to extract insights from large amounts of information. The identification of patterns is important because it may lead to a scientific discovery, an interpretation of clues to solve a crime, the prediction of catastrophic weather, a successful financial investment, or a better understanding of human behavior in a computermediated environment. Visualization technology shows considerable promise for increasing the value of large-scale collections of information, as evidenced by several commercial applications of TreeMap (e.g., http://www.smartmoney.com) and Hyperbolic tree (e.g., http://www.inxight.com) to visualize large-scale hierarchical structures. Although the proliferation of visualization technologies dates from the 1990s where sophisticated hardware and software made increasingly faster generation of graphical objects possible, the role of visual aids in facilitating the construction of mental images has a long history. Visualization has been used to communicate ideas, to monitor trends implicit in data, and to explore large volumes of data for hypothesis generation. Imagine traveling to a strange place without a map, having to memorize physical and chemical properties of an element without Mendeleyev's periodic table, trying to understand the stock market without statistical diagrams, or browsing a collection of documents without interactive visual aids. A collection of information can lose its value simply because of the effort required for exhaustive exploration. Such frustrations can be overcome by visualization.
Visualization can be classified as scientific visualization, software visualization, or information visualization. Although the data differ, the underlying techniques have much in common. They use the same elements (visual cues) and follow the same rules of combining visual cues to deliver patterns. They all involve understanding human perception (Encarnacao, Foley, Bryson, & Feiner, 1994) and require domain knowledge (Tufte, 1990). Because most decisions are based an unstructured information, such as text documents, Web pages, or e-mail messages, this chapter focuses an the visualization of unstructured textual documents. The chapter reviews information visualization techniques developed over the last decade and examines how they have been applied in different domains. The first section provides the background by describing visualization history and giving overviews of scientific, software, and information visualization as well as the perceptual aspects of visualization. The next section assesses important visualization techniques that convert abstract information into visual objects and facilitate navigation through displays an a computer screen. It also explores information analysis algorithms that can be applied to identify or extract salient visualizable structures from collections of information. Information visualization systems that integrate different types of technologies to address problems in different domains are then surveyed; and we move an to a survey and critique of visualization system evaluation studies. The chapter concludes with a summary and identification of future research directions.

Source

Annual review of information science and technology. 39(2005), S.139-177

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Source

Journal of information science. 18(1992), S.293-314

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Abstract

While the Web has become a worldwide platform for communication, terrorists share their ideology and communicate with members on the Dark Web - the reverse side of the Web used by terrorists. Currently, the problems of information overload and difficulty to obtain a comprehensive picture of terrorist activities hinder effective and efficient analysis of terrorist information on the Web. To improve understanding of terrorist activities, we have developed a novel methodology for collecting and analyzing Dark Web information. The methodology incorporates information collection, analysis, and visualization techniques, and exploits various Web information sources. We applied it to collecting and analyzing information of 39 Jihad Web sites and developed visualization of their site contents, relationships, and activity levels. An expert evaluation showed that the methodology is very useful and promising, having a high potential to assist in investigation and understanding of terrorist activities by producing results that could potentially help guide both policymaking and intelligence research.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.8, S.1347-1359

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Abstract

2 studies were conducted to investigate the cognitive processes involved in online document-based information retrieval. These studies led to the development of 5 computerised models of online document retrieval. These models were incorporated into a design of an 'intelligent' document-based retrieval system. Following a discussion of this system, discusses the broader implications of the research for the design of information retrieval sysems

Source

Information processing and management. 27(1991) no.5, S.405-432

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Abstract

Research in information retrieval (IR) has advanced significantly in the past few decades. Many tasks, such as indexing and text categorization, can be performed automatically with minimal human effort. Machine learning has played an important role in such automation by learning various patterns such as document topics, text structures, and user interests from examples. In recent years, it has become increasingly difficult to search for useful information an the World Wide Web because of its large size and unstructured nature. Useful information and resources are often hidden in the Web. While machine learning has been successfully applied to traditional IR systems, it poses some new challenges to apply these algorithms to the Web due to its large size, link structure, diversity in content and languages, and dynamic nature. On the other hand, such characteristics of the Web also provide interesting patterns and knowledge that do not present in traditional information retrieval systems.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.7, S.621-624

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Abstract

With more than two billion pages created by millions of Web page authors and organizations, the World Wide Web is a tremendously rich knowledge base. The knowledge comes not only from the content of the pages themselves, but also from the unique characteristics of the Web, such as its hyperlink structure and its diversity of content and languages. Analysis of these characteristics often reveals interesting patterns and new knowledge. Such knowledge can be used to improve users' efficiency and effectiveness in searching for information an the Web, and also for applications unrelated to the Web, such as support for decision making or business management. The Web's size and its unstructured and dynamic content, as well as its multilingual nature, make the extraction of useful knowledge a challenging research problem. Furthermore, the Web generates a large amount of data in other formats that contain valuable information. For example, Web server logs' information about user access patterns can be used for information personalization or improving Web page design.

Source

Annual review of information science and technology. 38(2004), S.289-330