@article {1972851, title = {Identity matching using personal and social identity features}, journal = {Information Systems Frontiers}, volume = {13}, year = {2011}, month = {2011}, pages = {101-113}, keywords = {BIS}, author = {Li,Jiexun and Wang,Alan Gang and Chen,Hsinchun} } @article {1973201, title = {Topological Analysis of Criminal Activity Networks: Enhancing Transportation Security}, journal = {IEEE Transactions on Intelligent Transportation Systems}, volume = {10}, year = {2009}, month = {2009}, pages = {83 - 91}, abstract = {The security of border and transportation systems is a critical component of the national strategy for homeland security. The security concerns at the border are not independent of law enforcement in border-area jurisdictions because the information known by local law enforcement agencies may provide valuable leads that are useful for securing the border and transportation infrastructure. The combined analysis of law enforcement information and data generated by vehicle license plate readers at international borders can be used to identify suspicious vehicles and people at ports of entry. This not only generates better quality leads for border protection agents but may also serve to reduce wait times for commerce, vehicles, and people as they cross the border. This paper explores the use of criminal activity networks (CANs) to analyze information from law enforcement and other sources to provide value for transportation and border security. We analyze the topological characteristics of CAN of individuals and vehicles in a multiple jurisdiction scenario. The advantages of exploring the relationships of individuals and vehicles are shown. We find that large narcotic networks are small world with short average path lengths ranging from 4.5 to 8.5 and have scale-free degree distributions with power law exponents of 0.85{\textendash}1.3. In addition, we find that utilizing information from multiple jurisdictions provides higher quality leads by reducing the average shortest-path lengths. The inclusion of vehicular relationships and border-crossing information generates more investigative leads that can aid in securing the border and transportation infrastructure.}, keywords = {Accounting, BIS}, url = {http://dx.doi.org/10.1109/TITS.2008.2011695}, author = {Kaza,Siddharth and Xu,Jennifer and Marshall,Byron and Chen,Hsinchun} } @article {1980851, title = {PRM-based identity matching using social context}, year = {2008}, month = {2008}, address = {Taipei, Taiwan}, keywords = {BIS}, author = {Li,Jiexun and Wang,Gang Alan and Chen,Hsinchun} } @article {1973206, title = {Using Importance Flooding to Identify Interesting Networks of Criminal Activity}, journal = {Journal of the Association for Information Science and Technology}, volume = {59}, year = {2008}, month = {2008}, pages = {2099-2114}, abstract = {Cross-jurisdictional law enforcement data sharing and analysis is of vital importance because law breakers regularly operate in multiple jurisdictions. Agencies continue to invest massive resources in various sharing initiatives despite several high-profile failures. Key difficulties include: privacy concerns, administrative issues, differences in data representation, and a need for better analysis tools. This work presents a methodology for sharing and analyzing investigation-relevant data and is potentially useful across large cross-jurisdictional data sets. The approach promises to allow crime analysts to use their time more effectively when creating link charts and performing similar analysis tasks. Many potential privacy and security pitfalls are avoided by reducing shared data requirements to labeled relationships between entities. Our importance flooding algorithm helps extract interesting networks of relationships from existing law enforcement records using user-controlled investigation heuristics, spreading activation, and path-based interestingness rules. In our experiments, several variations of the importance flooding approach outperformed relationship-weight-only methods in matching expert-selected associations. We find that accuracy in not substantially affected by reasonable variations in algorithm parameters and demonstrate that user feedback and additional, case-specific information can be usefully added to the computational model.}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_JASIST_ImportanceFlooding_PrePrint.pdf}, author = {Marshall,Byron and Chen,Hsinchun and Kaza,Siddharth} } @article {1980866, title = {Auto patent classification using citation network information: An experimental study in nanotechnology}, year = {2007}, month = {2007}, address = {Vancouver, British Columbia, Canada}, keywords = {BIS}, author = {Li,Xin and Chen,Hsinchun and Zhang,Zhu and Li,Jiexun} } @article {1980861, title = {Graph kernel-based learning for gene function prediction from gene interaction network}, year = {2007}, month = {2007}, address = {Fremont, CA, USA}, keywords = {BIS}, author = {Li,Xin and Zhang,Zhu and Chen,Hsinchun and Li,Jiexun} } @article {1972891, title = {Large-scale regulatory network analysis from microarray data: Modified Bayesian network learning and association rule mining}, journal = {Decision Support Systems}, volume = {43}, year = {2007}, month = {2007}, pages = {1207-1225}, keywords = {BIS}, author = {Huang,Zan and Li,Jiexun and Su,Hua and Watts,George S. and Chen,Hsinchun} } @article {1972896, title = {Optimal search-based gene subset selection for gene array cancer classification}, journal = {IEEE Transactions on Information Technology in Biomedicine}, volume = {11}, year = {2007}, month = {2007}, pages = {398-405}, keywords = {BIS}, author = {Li,Jiexun and Su,Hua and Chen,Hsinchun and Futscher,Bernard W.} } @article {1973211, title = {User-Centered Evaluation of Arizona BioPathway: An Information Extraction, Integration, and Visualization System}, journal = {IEEE Transactions on Information Technology in Biomedicine}, volume = {11}, year = {2007}, month = {2007}, pages = {527-536}, abstract = {Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This article presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature viewing method. Relation aggregation significantly contributes to knowledge acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multi-view, relation-based interface which supports user-controlled exploration of pathway information across multiple granularities.}, keywords = {Accounting, BIS}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=4300830\&arnumber=4300844\&count=17\&index=5}, author = {Qui{\~n}ones,Karin D. and Su,Hua and Marshall,Byron and Eggers,Shauna and Chen,Hsinchun} } @article {1973221, title = {Aggregating Automatically Extracted Regulatory Pathway Relations}, journal = {IEEE Transactions on Information Technology in Biomedicine}, volume = {10}, year = {2006}, month = {2006}, pages = {100- 108}, abstract = {Automatic tools to extract information from biomedical texts are needed to help researchers leverage the vast and increasing body of biomedical literature. While several biomedical relation extraction systems have been created and tested, little work has been done to meaningfully organize the extracted relations. Organizational processes should consolidate multiple references to the same objects over various levels of granularity, connect those references to other resources, and capture contextual information. We propose a feature decomposition approach to relation aggregation to support a five-level aggregation framework. Our BioAggregate tagger uses this approach to identify key features in extracted relation name strings. We show encouraging feature assignment accuracy and report substantial consolidation in a network of extracted relations.}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_IEEE_TITB_2005.pdf}, author = {Marshall,Byron and Su,Hua and McDonald,Daniel and Eggers,Shauna and Chen,Hsinchun} } @article {1980876, title = {A Bayesian framework of integrating gene functional relations from heterogeneous data sources}, year = {2006}, month = {2006}, address = {Phoenix, AZ, USA}, keywords = {BIS}, author = {Li,Jiexun and Li,Xin and Su,Hua and Chen,Hsinchun} } @article {1972911, title = {A framework of authorship identification for online messages: Writing style features and classification techniques}, journal = {Journal of the Association for Information Science and Technology}, volume = {57}, year = {2006}, month = {2006}, pages = {378-393}, keywords = {BIS}, author = {Zheng,Rong and Li,Jiexun and Chen,Hsinchun and Huang,Zan and Qin,Yi} } @article {1972901, title = {A framework of integrating gene functional relations from heterogeneous data sources: An experiment on Arabidopsis thaliana}, journal = {Bioinformatics}, volume = {22}, year = {2006}, month = {2006}, pages = {2037-2043}, keywords = {BIS}, author = {Li,Jiexun and Li,Xin and Su,Hua and Chen,Hsinchun and Galbraith,David W.} } @article {1972906, title = {From fingerprint to writeprint}, journal = {Communications of the ACM}, volume = {49}, year = {2006}, month = {2006}, pages = {76-82}, keywords = {BIS}, author = {Li,Jiexun and Zheng,Rong and Chen,Hsinchun} } @article {1973216, title = {Matching Knowledge Elements in Concept Maps Using a Similarity Flooding Algorithm}, journal = {Decision Support Systems}, volume = {42}, year = {2006}, month = {2006}, pages = {1290-1306}, abstract = {Concept mapping systems used in education and knowledge management emphasize flexibility of representation to enhance learning and facilitate knowledge capture. Collections of concept maps exhibit terminology variance, informality, and organizational variation. These factors make it difficult to match elements between maps in comparison, retrieval, and merging processes. In this work, we add an element anchoring mechanism to a similarity flooding (SF) algorithm to match nodes and substructures between pairs of simulated maps and student-drawn concept maps. Experimental results show significant improvement over simple string matching with combined recall accuracy of 91\% for conceptual nodes and concept {\textasciidieresis} link {\textasciidieresis} concept propositions in student-drawn maps.}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/MatchKnowledgeElements_PrePrintVersion.pdf}, author = {Marshall,Byron and Chen,Hsinchun and Madhusudan,Therani} } @article {1973226, title = {Moving Digital Libraries into the Student Learning Space: the GetSmart Experience}, journal = {Journal on Educational Resources in Computing}, volume = {6}, year = {2006}, month = {2006}, abstract = {The GetSmart system was built to support theoretically sound learning processes in a digital library environment by integrating course management, digital library, and concept mapping components to support a constructivist, six-step, information search process. In the fall of 2002 more than 100 students created 1400 concept maps as part of selected computing classes offered at the University of Arizona and Virginia Tech. Those students conducted searches, obtained course information, created concept maps, collaborated in acquiring knowledge, and presented their knowledge representations. This article connects the design elements of the GetSmart system to targeted concept-map-based learning processes, describes our system and research testbed, and analyzes our system usage logs. Results suggest that students did in fact use the tools in an integrated fashion, combining knowledge representation and search activities. After concept mapping was included in the curriculum, we observed improvement in students{\textquoteright} online quiz scores. Further, we observed that students in groups collaboratively constructed concept maps with multiple group members viewing and updating map details.}, keywords = {Accounting, BIS}, url = {http://portal.acm.org/citation.cfm?doid=1217862.1217864}, author = {Marshall,Byron and Chen,Hsinchun and Shen,Rao and Fox,Edward A.} } @article {1980881, title = {Optimal search-based gene subset selection for microarray cancer classification}, year = {2006}, month = {2006}, address = {Phoenix, AZ, USA}, keywords = {BIS}, author = {Li,Jiexun and Su,Hua and Chen,Hsinchun and Futscher,Bernard W} } @conference {1984601, title = {Using Importance Flooding to Identify Interesting Networks of Criminal Activity}, booktitle = {Proceedings of the IEEE International Conference on Intelligence and Security Informatics (ISI-2006), IEEE}, year = {2006}, month = {2006}, address = {San Diego, CA}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_ISI_2006.pdf}, author = {Marshall,Byron and Chen,Hsinchun} } @conference {1984606, title = {Linking Ontological Resources Using Aggregatable Substance Identifiers to Organize Extracted Relations}, booktitle = {Proceedings of the Pacific Symposium on Biocomputing, Jan 4-8, 2005, Big Island, Hawaii}, year = {2005}, month = {2005}, abstract = {Systems that extract biological regulatory pathway relations from free-text sources are
intended to help researchers leverage vast and growing collections of research literature.
Several systems to extract such relations have been developed but little work has focused on
how those relations can be usefully organized (aggregated) to support visualization systems or
analysis algorithms. Ontological resources that enumerate name strings for different types of
biomedical objects should play a key role in the organization process. In this paper we
delineate five potentially useful levels of relational granularity and propose the use of
aggregatable substance identifiers to help reduce lexical ambiguity. An aggregatable
substance identifier applies to a gene and its products. We merged 4 extensive lexicons and
compared the extracted strings to the text of five million MEDLINE abstracts. We report on
the ambiguity within and between name strings and common English words. Our results show
an 89\% reduction in ambiguity for the extracted human substance name strings when using an
aggregatable substance approach.}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/marshall_PSB2005.pdf}, author = {Marshall,Byron and Su,Hua and McDonald,Dan and Chen,Hsinchun} } @article {1980886, title = {Optimal search based gene selection for cancer prognosis}, year = {2005}, month = {2005}, address = {Omaha, NE}, keywords = {BIS}, author = {Li,Jiexun and Su,Hua and Chen,Hsinchun} } @conference {1984611, title = {Visualizing Aggregated Biological Pathway Relations}, booktitle = {Proceedings of the 2005 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2005), June 7-11, 2005 , Denver, CO}, year = {2005}, month = {2005}, abstract = {The Genescene development team has constructed an aggregation interface for automatically-extracted biomedical pathway
relations that is intended to help researchers identify and process relevant information from the vast digital library of abstracts found in the National Library of Medicine{\textquoteright}s PubMed collection.
Users view extracted relations at various levels of relational granularity in an interactive and visual node-link interface. Anecdotal feedback reported here suggests that this multigranular visual paradigm aligns well with various research tasks,
helping users find relevant articles and discover new information.}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_JCDL_2005_Aggregation.pdf}, author = {Marshall,Byron and Qui{\~n}ones,Karin and Su,Hua and Eggers,Shauna and Chen,Hsinchun} } @article {1973241, title = {EBizPort: Collecting and Analyzing Business Intelligence Information}, journal = {Journal of the Association for Information Science and Technology}, volume = {55}, year = {2004}, month = {2004}, pages = {873-891}, abstract = {In this article, Marshall, McDonald, Chen, and Chung take a different approach to supporting search services to large and heterogeneous document collections. They propose development of a domain-specific collection by crawling the content of a small set of highly reputable sites, maintaining a local index of the content, and providing browsing and searching services on the specialized content. This resource, known as a vertical portal, has the potential of overcoming several problems associated with bias, update delay, reputation, and integration of scattered information. The article discusses the design of a vertical portal system{\textquoteright}s architecture called EbizPort, rationale behind its major components, and algorithms and techniques for building collections and search functions. Collection (or more broadly content) has an obvious relationship to the nature of the search interface, as it can impact the type of search functions that can be offered. Powerful search interface functions were built for EbizPort by exploiting the underlying content representation and a relatively narrow and well-defined domain focus. Particularly noteworthy are the innovative browsing functions, which include a summarizer, a categorizer, a visualizer, and a navigation side-bar. The article ends with a discussion of an evaluation study, which compared the EbizPort system with a baseline system called Brint. Results are presented on effectiveness and efficiency, usability and information quality, and quality of local collection and content retrieved from other sources (an extended search operation called meta-search service was also provided in the system). Overall, the authors find that EbizPort outperforms the baseline system, and it provides a viable way to support access to business information.}, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_JASIST_EBizPort.pdf}, author = {Marshall,Byron and McDonald,Dan and Chen,Hsinchun and Chung,Wingyan} } @article {1973231, title = {Extracting Gene Pathway Relations Using a Hybrid Grammar: The Arizona Relation Parser}, journal = {Bioinformatics}, volume = {20}, year = {2004}, month = {2004}, pages = {3370-8}, abstract = {Motivation: Text-mining research in the biomedical domain has been motivated by the rapid growth of new research findings. Improving the accessibility of findings has potential to speed hypothesis generation.Results: We present the Arizona Relation Parser that differs from other parsers in its use of a broad coverage syntax-semantic hybrid grammar. While syntax grammars have generally been tested over more documents, semantic grammars have outperformed them in precision and recall. We combined access to syntax and semantic information from a single grammar. The parser was trained using 40 PubMed abstracts and then tested using 100 unseen abstracts, half for precision and half for recall. Expert evaluation showed that the parser extracted biologically relevant relations with 89\% precision. Recall of expert identified relations with semantic filtering was 35 and 61\% before semantic filtering. Such results approach the higher-performing semantic parsers. However, the AZ parser was tested over a greater variety of writing styles and semantic content. }, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/MCDONALD_BIOINFORMATICS.pdf}, author = {McDonald,Dan and Chen,Hsinchun and Su,Hua and Marshall,Byron} } @article {1980891, title = {Genescene: Biomedical text and data mining}, year = {2003}, month = {2003}, address = {Houston, TX, USA}, keywords = {BIS}, author = {Leroy,Gondy and Chen,Hsinchun and Martinez,Jessie and Eggers,S and Falsey,R and Kislin,K and Huang,Zan and Li,Jiexun and Xu,Jennifer and McDonald,Daniel and Ng,Gavin} } @conference {1973246, title = {Knowledge Management and E-Learning: the GetSmart Experience}, booktitle = {Proceedings of the 2003 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2003), May 2003, Houston, Texas}, year = {2003}, month = {2003}, abstract = {The National Science Digital Library (NSDL), launched in December 2002, is emerging as a center of innovation in digital libraries as applied to education. As a part of this extensive project, the GetSmart system was created to apply knowledge management techniques in a learning environment. The design of the system is based on an analysis of learning theory and theinformation search process. Its key notion is the integration of search tools and curriculum support with concept mapping. More than 100 students at the University of Arizona and Virginia Tech used the system in the fall of 2002. A database of more than one thousand student-prepared concept maps has been collected with more than forty thousand relationships expressed in semantic, graphical, node-link representations. Preliminary analysis of the collected data is revealing interesting knowledge representation patterns. }, keywords = {Accounting, BIS}, url = {http://people.oregonstate.edu/~marshaby/Papers/Marshall_JCDL2003_GetSmart.pdf}, author = {Marshall,Byron and Zhang,Yiwen and Chen,Hsinchun and Lally,Ann and Shen,Rao and Fox,Edward and Cassel,Lillian} }