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  • × author_ss:"Chen, H."
  • × year_i:[2000 TO 2010}
  1. Chen, H.; Chau, M.: Web mining : machine learning for Web applications (2003) 0.00
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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.
    Type
    a
  2. Schroeder, J.; Xu, J.; Chen, H.; Chau, M.: Automated criminal link analysis based on domain knowledge (2007) 0.00
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    Abstract
    Link (association) analysis has been used in the criminal justice domain to search large datasets for associations between crime entities in order to facilitate crime investigations. However, link analysis still faces many challenging problems, such as information overload, high search complexity, and heavy reliance on domain knowledge. To address these challenges, this article proposes several techniques for automated, effective, and efficient link analysis. These techniques include the co-occurrence analysis, the shortest path algorithm, and a heuristic approach to identifying associations and determining their importance. We developed a prototype system called CrimeLink Explorer based on the proposed techniques. Results of a user study with 10 crime investigators from the Tucson Police Department showed that our system could help subjects conduct link analysis more efficiently than traditional single-level link analysis tools. Moreover, subjects believed that association paths found based on the heuristic approach were more accurate than those found based solely on the co-occurrence analysis and that the automated link analysis system would be of great help in crime investigations.
    Type
    a
  3. Marshall, B.; McDonald, D.; Chen, H.; Chung, W.: EBizPort: collecting and analyzing business intelligence information (2004) 0.00
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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.
    Type
    a
  4. Vishwanath, A.; Chen, H.: Technology clusters : using multidimensional scaling to evaluate and structure technology clusters (2006) 0.00
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    Abstract
    Empirical evidence suggests that the ownership of related products that form a technology cluster is signifIcantly better than the attributes of an innovation at predicting adoption. The treatment of technology clusters, however, has been ad hoc and study specific: Researchers often make a priori assumptions about the relationships between technologies and measure ownership using lists of functionally related technology, without any systematic reasoning. Hence, the authors set out to examine empirically the composition of technology clusters and the differences, if any, in clusters of technologies formed by adopters and nonadopters. Using the Galileo system of multidimensional scaling and the associational diffusion framework, the dissimilarities between 30 technology concepts were scored by adopters and nonadopters. Results indicate clear differences in conceptualization of clusters: Adopters tend to relate technologies based an their functional similarity; here, innovations are perceived to be complementary, and hence, adoption of one technology spurs the adoption of related technologies. On the other hand, nonadopters tend to relate technologies using a stricter ascendancy of association where the adoption of an innovation makes subsequent innovations redundant. The results question the measurement approaches and present an alternative methodology.
    Type
    a
  5. Chen, H.; Fan, H.; Chau, M.; Zeng, D.: MetaSpider : meta-searching and categorization on the Web (2001) 0.00
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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.
    Type
    a
  6. Marshall, B.; Chen, H.; Kaza, S.: Using importance flooding to identify interesting networks of criminal activity (2008) 0.00
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    Abstract
    Effectively harnessing available data to support homeland-security-related applications is a major focus in the emerging science of intelligence and security informatics (ISI). Many studies have focused on criminal-network analysis as a major challenge within the ISI domain. Though various methodologies have been proposed, none have been tested for usefulness in creating link charts. This study compares manually created link charts to suggestions made by the proposed importance-flooding algorithm. Mirroring manual investigational processes, our iterative computation employs association-strength metrics, incorporates path-based node importance heuristics, allows for case-specific notions of importance, and adjusts based on the accuracy of previous suggestions. Interesting items are identified by leveraging both node attributes and network structure in a single computation. Our data set was systematically constructed from heterogeneous sources and omits many privacy-sensitive data elements such as case narratives and phone numbers. The flooding algorithm improved on both manual and link-weight-only computations, and our results suggest that the approach is robust across different interpretations of the user-provided heuristics. This study demonstrates an interesting methodology for including user-provided heuristics in network-based analysis, and can help guide the development of ISI-related analysis tools.
    Type
    a
  7. Chen, H.: Intelligence and security informatics : Introduction to the special topic issue (2005) 0.00
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    Abstract
    Making the Nation Safer: The Role of Science and Technology in Countering Terrorism The commitment of the scientific, engineering, and health communities to helping the United States and the world respond to security challenges became evident after September 11, 2001. The U.S. National Research Council's report an "Making the Nation Safer: The Role of Science and Technology in Countering Terrorism," (National Research Council, 2002, p. 1) explains the context of such a new commitment: Terrorism is a serious threat to the Security of the United States and indeed the world. The vulnerability of societies to terrorist attacks results in part from the proliferation of chemical, biological, and nuclear weapons of mass destruction, but it also is a consequence of the highly efficient and interconnected systems that we rely an for key services such as transportation, information, energy, and health care. The efficient functioning of these systems reflects great technological achievements of the past century, but interconnectedness within and across systems also means that infrastructures are vulnerable to local disruptions, which could lead to widespread or catastrophic failures. As terrorists seek to exploit these vulnerabilities, it is fitting that we harness the nation's exceptional scientific and technological capabilities to Counter terrorist threats. A committee of 24 of the leading scientific, engineering, medical, and policy experts in the United States conducted the study described in the report. Eight panels were separately appointed and asked to provide input to the committee. The panels included: (a) biological sciences, (b) chemical issues, (c) nuclear and radiological issues, (d) information technology, (e) transportation, (f) energy facilities, Cities, and fixed infrastructure, (g) behavioral, social, and institutional issues, and (h) systems analysis and systems engineering. The focus of the committee's work was to make the nation safer from emerging terrorist threats that sought to inflict catastrophic damage an the nation's people, its infrastructure, or its economy. The committee considered nine areas, each of which is discussed in a separate chapter in the report: nuclear and radiological materials, human and agricultural health systems, toxic chemicals and explosive materials, information technology, energy systems, transportation systems, Cities and fixed infrastructure, the response of people to terrorism, and complex and interdependent systems. The chapter an information technology (IT) is particularly relevant to this special issue. The report recommends that "a strategic long-term research and development agenda should be established to address three primary counterterrorismrelated areas in IT: information and network security, the IT needs of emergency responders, and information fusion and management" (National Research Council, 2002, pp. 11 -12). The MD in information and network security should include approaches and architectures for prevention, identification, and containment of cyber-intrusions and recovery from them. The R&D to address IT needs of emergency responders should include ensuring interoperability, maintaining and expanding communications capability during an emergency, communicating with the public during an emergency, and providing support for decision makers. The R&D in information fusion and management for the intelligence, law enforcement, and emergency response communities should include data mining, data integration, language technologies, and processing of image and audio data. Much of the research reported in this special issue is related to information fusion and management for homeland security.
    Type
    a
  8. Dang, Y.; Zhang, Y.; Chen, H.; Hu, P.J.-H.; Brown, S.A.; Larson, C.: Arizona Literature Mapper : an integrated approach to monitor and analyze global bioterrorism research literature (2009) 0.00
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    Abstract
    Biomedical research is critical to biodefense, which is drawing increasing attention from governments globally as well as from various research communities. The U.S. government has been closely monitoring and regulating biomedical research activities, particularly those studying or involving bioterrorism agents or diseases. Effective surveillance requires comprehensive understanding of extant biomedical research and timely detection of new developments or emerging trends. The rapid knowledge expansion, technical breakthroughs, and spiraling collaboration networks demand greater support for literature search and sharing, which cannot be effectively supported by conventional literature search mechanisms or systems. In this study, we propose an integrated approach that integrates advanced techniques for content analysis, network analysis, and information visualization. We design and implement Arizona Literature Mapper, a Web-based portal that allows users to gain timely, comprehensive understanding of bioterrorism research, including leading scientists, research groups, institutions as well as insights about current mainstream interests or emerging trends. We conduct two user studies to evaluate Arizona Literature Mapper and include a well-known system for benchmarking purposes. According to our results, Arizona Literature Mapper is significantly more effective for supporting users' search of bioterrorism publications than PubMed. Users consider Arizona Literature Mapper more useful and easier to use than PubMed. Users are also more satisfied with Arizona Literature Mapper and show stronger intentions to use it in the future. Assessments of Arizona Literature Mapper's analysis functions are also positive, as our subjects consider them useful, easy to use, and satisfactory. Our results have important implications that are also discussed in the article.
    Type
    a
  9. Chen, H.: Introduction to the JASIST special topic section on Web retrieval and mining : A machine learning perspective (2003) 0.00
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    a