-
Chen, H.; Shankaranarayanan, G.; She, L.: ¬A machine learning approach to inductive query by examples : an experiment using relevance feedback, ID3, genetic algorithms, and simulated annealing (1998)
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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
-
Qin, J.; Zhou, Y.; Chau, M.; Chen, H.: Multilingual Web retrieval : an experiment in English-Chinese business intelligence (2006)
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- Abstract
- As increasing numbers of non-English resources have become available on the Web, the interesting and important issue of how Web users can retrieve documents in different languages has arisen. Cross-language information retrieval (CLIP), the study of retrieving information in one language by queries expressed in another language, is a promising approach to the problem. Cross-language information retrieval has attracted much attention in recent years. Most research systems have achieved satisfactory performance on standard Text REtrieval Conference (TREC) collections such as news articles, but CLIR techniques have not been widely studied and evaluated for applications such as Web portals. In this article, the authors present their research in developing and evaluating a multilingual English-Chinese Web portal that incorporates various CLIP techniques for use in the business domain. A dictionary-based approach was adopted and combines phrasal translation, co-occurrence analysis, and pre- and posttranslation query expansion. The portal was evaluated by domain experts, using a set of queries in both English and Chinese. The experimental results showed that co-occurrence-based phrasal translation achieved a 74.6% improvement in precision over simple word-byword translation. When used together, pre- and posttranslation query expansion improved the performance slightly, achieving a 78.0% improvement over the baseline word-by-word translation approach. In general, applying CLIR techniques in Web applications shows promise.
- Footnote
- Beitrag einer special topic section on multilingual information systems
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.5, S.671-683
-
Dumais, S.; Chen, H.: Hierarchical classification of Web content (2000)
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- Source
- Proceedings of ACM SIGIR 23rd International Conference on Research and Development in Information Retrieval. Ed. by N.J. Belkin, P. Ingwersen u. M.K. Leong
- Theme
- Klassifikationssysteme im Online-Retrieval
-
Schatz, B.R.; Johnson, E.H.; Cochrane, P.A.; Chen, H.: Interactive term suggestion for users of digital libraries : using thesauri and co-occurrence lists for information retrieval (1996)
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- Source
- Proceedings of the 1st ACM International Conference on Digital Libraries
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Chen, H.; Houston, A.L.; Sewell, R.R.; Schatz, B.R.: Internet browsing and searching : user evaluations of category map and concept space techniques (1998)
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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
-
Chen, H.; Yim, T.; Fye, D.: Automatic thesaurus generation for an electronic community system (1995)
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- Abstract
- Reports an algorithmic approach to the automatic generation of thesauri for electronic community systems. The techniques used included terms filtering, automatic indexing, and cluster analysis. The testbed for the research was the Worm Community System, which contains a comprehensive library of specialized community data and literature, currently in use by molecular biologists who study the nematode worm. The resulting worm thesaurus included 2709 researchers' names, 798 gene names, 20 experimental methods, and 4302 subject descriptors. On average, each term had about 90 weighted neighbouring terms indicating relevant concepts. The thesaurus was developed as an online search aide. Tests the worm thesaurus in an experiment with 6 worm researchers of varying degrees of expertise and background. The experiment showed that the thesaurus was an excellent 'memory jogging' device and that it supported learning and serendipitous browsing. Despite some occurrences of obvious noise, the system was useful in suggesting relevant concepts for the researchers' queries and it helped improve concept recall. With a simple browsing interface, an automatic thesaurus can become a useful tool for online search and can assist researchers in exploring and traversing a dynamic and complex electronic community system
- Source
- Journal of the American Society for Information Science. 46(1995) no.3, S.175-193
- Theme
- Verbale Doksprachen im Online-Retrieval
-
Chen, H.: Machine learning for information retrieval : neural networks, symbolic learning, and genetic algorithms (1994)
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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
-
Chen, H.; Lally, A.M.; Zhu, B.; Chau, M.: HelpfulMed : Intelligent searching for medical information over the Internet (2003)
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- Abstract
- The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.
- Footnote
- Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"
- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.7, S.683-694
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
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Chen, H.; Dhar, V.: Cognitive process as a basis for intelligent retrieval system design (1991)
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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
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Chen, H.: Introduction to the JASIST special topic section on Web retrieval and mining : A machine learning perspective (2003)
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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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Huang, Z.; Chung, Z.W.; Chen, H.: ¬A graph model for e-commerce recommender systems (2004)
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- Abstract
- Information overload on the Web has created enormous challenges to customers selecting products for online purchases and to online businesses attempting to identify customers' preferences efficiently. Various recommender systems employing different data representations and recommendation methods are currently used to address these challenges. In this research, we developed a graph model that provides a generic data representation and can support different recommendation methods. To demonstrate its usefulness and flexibility, we developed three recommendation methods: direct retrieval, association mining, and high-degree association retrieval. We used a data set from an online bookstore as our research test-bed. Evaluation results showed that combining product content information and historical customer transaction information achieved more accurate predictions and relevant recommendations than using only collaborative information. However, comparisons among different methods showed that high-degree association retrieval did not perform significantly better than the association mining method or the direct retrieval method in our test-bed.
- Source
- Journal of the American Society for Information Science and technology. 55(2004) no.3, S.259-274
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Chen, H.; Ng, T.D.; Martinez, J.; Schatz, B.R.: ¬A concept space approach to addressing the vocabulary problem in scientific information retrieval : an experiment on the Worm Community System (1997)
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- Abstract
- This research presents an algorithmic approach to addressing the vocabulary problem in scientific information retrieval and information sharing, using the molecular biology domain as an example. We first present a literature review of cognitive studies related to the vocabulary problem and vocabulary-based search aids (thesauri) and then discuss techniques for building robust and domain-specific thesauri to assist in cross-domain scientific information retrieval. Using a variation of the automatic thesaurus generation techniques, which we refer to as the concept space approach, we recently conducted an experiment in the molecular biology domain in which we created a C. elegans worm thesaurus of 7.657 worm-specific terms and a Drosophila fly thesaurus of 15.626 terms. About 30% of these terms overlapped, which created vocabulary paths from one subject domain to the other. Based on a cognitve study of term association involving 4 biologists, we found that a large percentage (59,6-85,6%) of the terms suggested by the subjects were identified in the cojoined fly-worm thesaurus. However, we found only a small percentage (8,4-18,1%) of the associations suggested by the subjects in the thesaurus
- Source
- Journal of the American Society for Information Science. 48(1997) no.1, S.17-31
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Chen, H.: Knowledge-based document retrieval : framework and design (1992)
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- Source
- Journal of information science. 18(1992), S.293-314
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Zhu, B.; Chen, H.: Validating a geographical image retrieval system (2000)
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- Abstract
- This paper summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. By using an image as its interface, the prototype system addresses a troublesome aspect of traditional retrieval models, which require users to have complete knowledge of the low-level features of an image. In addition we describe an experiment to validate against that of human subjects in an effort to address the scarcity of research evaluating performance of an algorithm against that of human beings. The results of the experiment indicate that the system could do as well as human subjects in accomplishing the tasks of similarity analysis and image categorization. We also found that under some circumstances texture features of an image are insufficient to represent an geographic image. We believe, however, that our image retrieval system provides a promising approach to integrating image processing techniques and information retrieval algorithms
- Source
- Journal of the American Society for Information Science. 51(2000) no.7, S.625-634
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Chen, H.: ¬An analysis of image queries in the field of art history (2001)
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- Abstract
- Chen arranged with an Art History instructor to require 20 medieval art images in papers received from 29 students. Participants completed a self administered presearch and postsearch questionnaire, and were interviewed after questionnaire analysis, in order to collect both the keywords and phrases they planned to use, and those actually used. Three MLIS student reviewers then mapped the queries to Enser and McGregor's four categories, Jorgensen's 12 classes, and Fidel's 12 feature data and object poles providing a degree of match on a seven point scale (one not at all to 7 exact). The reviewers give highest scores to Enser and McGregor;'s categories. Modifications to both the Enser and McGregor and Jorgensen schemes are suggested
- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.3, S.260-273
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Vishwanath, A.; Chen, H.: Personal communication technologies as an extension of the self : a cross-cultural comparison of people's associations with technology and their symbolic proximity with others (2008)
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- Abstract
- Increasingly, individuals use communication technologies such as e-mail, IMs, blogs, and cell phones to locate, learn about, and communicate with one another. Not much, however, is known about how individuals relate to various personal technologies, their preferences for each, or their extensional associations with them. Even less is known about the cultural differences in these preferences. The current study used the Galileo system of multidimensional scaling to systematically map the extensional associations with nine personal communication technologies across three cultures: U.S., Germany, and Singapore. Across the three cultures, the technologies closest to the self were similar, suggesting a universality of associations with certain technologies. In contrast, the technologies farther from the self were significantly different across cultures. Moreover, the magnitude of associations with each technology differed based on the extensional association or distance from the self. Also, and more importantly, the antecedents to these associations differed significantly across cultures, suggesting a stronger influence of cultural norms on personal-technology choice.
- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.11, S.1761-1775
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Chau, M.; Wong, C.H.; Zhou, Y.; Qin, J.; Chen, H.: Evaluating the use of search engine development tools in IT education (2010)
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- Abstract
- It is important for education in computer science and information systems to keep up to date with the latest development in technology. With the rapid development of the Internet and the Web, many schools have included Internet-related technologies, such as Web search engines and e-commerce, as part of their curricula. Previous research has shown that it is effective to use search engine development tools to facilitate students' learning. However, the effectiveness of these tools in the classroom has not been evaluated. In this article, we review the design of three search engine development tools, SpidersRUs, Greenstone, and Alkaline, followed by an evaluation study that compared the three tools in the classroom. In the study, 33 students were divided into 13 groups and each group used the three tools to develop three independent search engines in a class project. Our evaluation results showed that SpidersRUs performed better than the two other tools in overall satisfaction and the level of knowledge gained in their learning experience when using the tools for a class project on Internet applications development.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.2, S.288-299
-
Li, J.; Zhang, Z.; Li, X.; Chen, H.: Kernel-based learning for biomedical relation extraction (2008)
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- Abstract
- Relation extraction is the process of scanning text for relationships between named entities. Recently, significant studies have focused on automatically extracting relations from biomedical corpora. Most existing biomedical relation extractors require manual creation of biomedical lexicons or parsing templates based on domain knowledge. In this study, we propose to use kernel-based learning methods to automatically extract biomedical relations from literature text. We develop a framework of kernel-based learning for biomedical relation extraction. In particular, we modified the standard tree kernel function by incorporating a trace kernel to capture richer contextual information. In our experiments on a biomedical corpus, we compare different kernel functions for biomedical relation detection and classification. The experimental results show that a tree kernel outperforms word and sequence kernels for relation detection, our trace-tree kernel outperforms the standard tree kernel, and a composite kernel outperforms individual kernels for relation extraction.
- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.5, S.756-769
-
Jiang, S.; Gao, Q.; Chen, H.; Roco, M.C.: ¬The roles of sharing, transfer, and public funding in nanotechnology knowledge-diffusion networks (2015)
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- Abstract
- Understanding the knowledge-diffusion networks of patent inventors can help governments and businesses effectively use their investment to stimulate commercial science and technology development. Such inventor networks are usually large and complex. This study proposes a multidimensional network analysis framework that utilizes Exponential Random Graph Models (ERGMs) to simultaneously model knowledge-sharing and knowledge-transfer processes, examine their interactions, and evaluate the impacts of network structures and public funding on knowledge-diffusion networks. Experiments are conducted on a longitudinal data set that covers 2 decades (1991-2010) of nanotechnology-related US Patent and Trademark Office (USPTO) patents. The results show that knowledge sharing and knowledge transfer are closely interrelated. High degree centrality or boundary inventors play significant roles in the network, and National Science Foundation (NSF) public funding positively affects knowledge sharing despite its small fraction in overall funding and upstream research topics.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.5, S.1017-1029
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Chung, W.; Chen, H.: Browsing the underdeveloped Web : an experiment on the Arabic Medical Web Directory (2009)
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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
