TY - JOUR T1 - The information content of mandatory risk factor disclosures in corporate filings JF - Review of Accounting Studies Y1 - 2014 A1 - Steele,Logan A1 - Campbell,John A1 - Chen,Hsinchun A1 - Dhaliwal,Dan A1 - Lu,Hsin-min KW - Accounting VL - 19 CP - 1 U2 - a U4 - 167853649920 ID - 167853649920 ER - TY - JOUR T1 - Identity matching using personal and social identity features JF - Information Systems Frontiers Y1 - 2011 A1 - Li,Jiexun A1 - Wang,Alan Gang A1 - Chen,Hsinchun KW - BIS VL - 13 CP - 1 U2 - a U4 - 86816591872 ID - 86816591872 ER - TY - JOUR T1 - Topological Analysis of Criminal Activity Networks: Enhancing Transportation Security JF - IEEE Transactions on Intelligent Transportation Systems Y1 - 2009 A1 - Kaza,Siddharth A1 - Xu,Jennifer A1 - Marshall,Byron A1 - Chen,Hsinchun KW - Accounting KW - BIS AB - 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 0.85–1.3. 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. VL - 10 UR - http://dx.doi.org/10.1109/TITS.2008.2011695 CP - 1 U2 - a U4 - 2609299457 ID - 2609299457 ER - TY - HEAR T1 - PRM-based identity matching using social context Y1 - 2008 A1 - Li,Jiexun A1 - Wang,Gang Alan A1 - Chen,Hsinchun KW - BIS JA - IEEE International Conference on Intelligence and Security Informatics (ISI 2008) CY - Taipei, Taiwan U2 - c U4 - 98583906304 ID - 98583906304 ER - TY - JOUR T1 - Using Importance Flooding to Identify Interesting Networks of Criminal Activity JF - Journal of the Association for Information Science and Technology Y1 - 2008 A1 - Marshall,Byron A1 - Chen,Hsinchun A1 - Kaza,Siddharth KW - Accounting KW - BIS AB - 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. VL - 59 UR - http://people.oregonstate.edu/~marshaby/Papers/Marshall_JASIST_ImportanceFlooding_PrePrint.pdf CP - 13 U2 - a U4 - 2609309697 ID - 2609309697 ER - TY - HEAR T1 - Auto patent classification using citation network information: An experimental study in nanotechnology Y1 - 2007 A1 - Li,Xin A1 - Chen,Hsinchun A1 - Zhang,Zhu A1 - Li,Jiexun KW - BIS JA - ACM/IEEE Joint Conference on Digital Libraries (JCDL 2007) CY - Vancouver, British Columbia, Canada U2 - c U4 - 98583994368 ID - 98583994368 ER - TY - HEAR T1 - Graph kernel-based learning for gene function prediction from gene interaction network Y1 - 2007 A1 - Li,Xin A1 - Zhang,Zhu A1 - Chen,Hsinchun A1 - Li,Jiexun KW - BIS JA - IEEE International Conference on Bioinformatics and Biomedicine (IEEE-BIBM 2007) CY - Fremont, CA, USA U2 - c U4 - 98583965696 ID - 98583965696 ER - TY - JOUR T1 - Large-scale regulatory network analysis from microarray data: Modified Bayesian network learning and association rule mining JF - Decision Support Systems Y1 - 2007 A1 - Huang,Zan A1 - Li,Jiexun A1 - Su,Hua A1 - Watts,George S. A1 - Chen,Hsinchun KW - BIS VL - 43 U2 - a U4 - 86818299904 ID - 86818299904 ER - TY - JOUR T1 - Optimal search-based gene subset selection for gene array cancer classification JF - IEEE Transactions on Information Technology in Biomedicine Y1 - 2007 A1 - Li,Jiexun A1 - Su,Hua A1 - Chen,Hsinchun A1 - Futscher,Bernard W. KW - BIS VL - 11 CP - 4 U2 - a U4 - 86818201600 ID - 86818201600 ER - TY - JOUR T1 - User-Centered Evaluation of Arizona BioPathway: An Information Extraction, Integration, and Visualization System JF - IEEE Transactions on Information Technology in Biomedicine Y1 - 2007 A1 - Quiñones,Karin D. A1 - Su,Hua A1 - Marshall,Byron A1 - Eggers,Shauna A1 - Chen,Hsinchun KW - Accounting KW - BIS AB - 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. VL - 11 UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=4300830&arnumber=4300844&count=17&index=5 CP - 5 U2 - a U4 - 648212480 ID - 648212480 ER - TY - JOUR T1 - Aggregating Automatically Extracted Regulatory Pathway Relations JF - IEEE Transactions on Information Technology in Biomedicine Y1 - 2006 A1 - Marshall,Byron A1 - Su,Hua A1 - McDonald,Daniel A1 - Eggers,Shauna A1 - Chen,Hsinchun KW - Accounting KW - BIS AB - 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. VL - 10 UR - http://people.oregonstate.edu/~marshaby/Papers/Marshall_IEEE_TITB_2005.pdf CP - 1 U2 - a U4 - 648208384 ID - 648208384 ER - TY - HEAR T1 - A Bayesian framework of integrating gene functional relations from heterogeneous data sources Y1 - 2006 A1 - Li,Jiexun A1 - Li,Xin A1 - Su,Hua A1 - Chen,Hsinchun KW - BIS JA - American Medical Informatics Association (AMIA) Spring Congress CY - Phoenix, AZ, USA U2 - c U4 - 98584031232 ID - 98584031232 ER - TY - JOUR T1 - A framework of authorship identification for online messages: Writing style features and classification techniques JF - Journal of the Association for Information Science and Technology Y1 - 2006 A1 - Zheng,Rong A1 - Li,Jiexun A1 - Chen,Hsinchun A1 - Huang,Zan A1 - Qin,Yi KW - BIS VL - 57 CP - 3 U2 - a U4 - 86818478080 ID - 86818478080 ER - TY - JOUR T1 - A framework of integrating gene functional relations from heterogeneous data sources: An experiment on Arabidopsis thaliana JF - Bioinformatics Y1 - 2006 A1 - Li,Jiexun A1 - Li,Xin A1 - Su,Hua A1 - Chen,Hsinchun A1 - Galbraith,David W. KW - BIS VL - 22 CP - 16 U2 - a U4 - 86818365440 ID - 86818365440 ER - TY - JOUR T1 - From fingerprint to writeprint JF - Communications of the ACM Y1 - 2006 A1 - Li,Jiexun A1 - Zheng,Rong A1 - Chen,Hsinchun KW - BIS VL - 49 CP - 4 U2 - a U4 - 86818414592 ID - 86818414592 ER - TY - JOUR T1 - Matching Knowledge Elements in Concept Maps Using a Similarity Flooding Algorithm JF - Decision Support Systems Y1 - 2006 A1 - Marshall,Byron A1 - Chen,Hsinchun A1 - Madhusudan,Therani KW - Accounting KW - BIS AB - 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 ¨ link ¨ concept propositions in student-drawn maps. VL - 42 UR - http://people.oregonstate.edu/~marshaby/Papers/MatchKnowledgeElements_PrePrintVersion.pdf CP - 3 U2 - a U4 - 648204288 ID - 648204288 ER - TY - JOUR T1 - Moving Digital Libraries into the Student Learning Space: the GetSmart Experience JF - Journal on Educational Resources in Computing Y1 - 2006 A1 - Marshall,Byron A1 - Chen,Hsinchun A1 - Shen,Rao A1 - Fox,Edward A. KW - Accounting KW - BIS AB - 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' online quiz scores. Further, we observed that students in groups collaboratively constructed concept maps with multiple group members viewing and updating map details. VL - 6 UR - http://portal.acm.org/citation.cfm?doid=1217862.1217864 CP - 1 U2 - a U4 - 648214528 ID - 648214528 ER - TY - HEAR T1 - Optimal search-based gene subset selection for microarray cancer classification Y1 - 2006 A1 - Li,Jiexun A1 - Su,Hua A1 - Chen,Hsinchun A1 - Futscher,Bernard W KW - BIS JA - American Medical Informatics Association (AMIA) Spring Congress CY - Phoenix, AZ, USA U2 - c U4 - 98584055808 ID - 98584055808 ER - TY - CONF T1 - Using Importance Flooding to Identify Interesting Networks of Criminal Activity T2 - Proceedings of the IEEE International Conference on Intelligence and Security Informatics (ISI-2006), IEEE Y1 - 2006 A1 - Marshall,Byron A1 - Chen,Hsinchun KW - Accounting KW - BIS JA - Proceedings of the IEEE International Conference on Intelligence and Security Informatics (ISI-2006), IEEE CY - San Diego, CA UR - http://people.oregonstate.edu/~marshaby/Papers/Marshall_ISI_2006.pdf U2 - b U4 - 2606608385 ID - 2606608385 ER - TY - CONF T1 - Linking Ontological Resources Using Aggregatable Substance Identifiers to Organize Extracted Relations T2 - Proceedings of the Pacific Symposium on Biocomputing, Jan 4-8, 2005, Big Island, Hawaii Y1 - 2005 A1 - Marshall,Byron A1 - Su,Hua A1 - McDonald,Dan A1 - Chen,Hsinchun KW - Accounting KW - BIS AB - 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. JA - Proceedings of the Pacific Symposium on Biocomputing, Jan 4-8, 2005, Big Island, Hawaii UR - http://people.oregonstate.edu/~marshaby/Papers/marshall_PSB2005.pdf U2 - b U4 - 2606753793 ID - 2606753793 ER - TY - HEAR T1 - Optimal search based gene selection for cancer prognosis Y1 - 2005 A1 - Li,Jiexun A1 - Su,Hua A1 - Chen,Hsinchun KW - BIS JA - Americas Conference on Information Systems (AMCIS’05) CY - Omaha, NE U2 - c U4 - 98584080384 ID - 98584080384 ER - TY - CONF T1 - Visualizing Aggregated Biological Pathway Relations T2 - Proceedings of the 2005 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2005), June 7-11, 2005 , Denver, CO Y1 - 2005 A1 - Marshall,Byron A1 - Quiñones,Karin A1 - Su,Hua A1 - Eggers,Shauna A1 - Chen,Hsinchun KW - Accounting KW - BIS AB - 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’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. JA - Proceedings of the 2005 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2005), June 7-11, 2005 , Denver, CO UR - http://people.oregonstate.edu/~marshaby/Papers/Marshall_JCDL_2005_Aggregation.pdf U2 - b U4 - 2606727169 ID - 2606727169 ER - TY - JOUR T1 - EBizPort: Collecting and Analyzing Business Intelligence Information JF - Journal of the Association for Information Science and Technology Y1 - 2004 A1 - Marshall,Byron A1 - McDonald,Dan A1 - Chen,Hsinchun A1 - Chung,Wingyan KW - Accounting KW - BIS AB - 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'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. VL - 55 UR - http://people.oregonstate.edu/~marshaby/Papers/Marshall_JASIST_EBizPort.pdf CP - 1 U2 - a U4 - 648210432 ID - 648210432 ER - TY - JOUR T1 - Extracting Gene Pathway Relations Using a Hybrid Grammar: The Arizona Relation Parser JF - Bioinformatics Y1 - 2004 A1 - McDonald,Dan A1 - Chen,Hsinchun A1 - Su,Hua A1 - Marshall,Byron KW - Accounting KW - BIS AB - 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. VL - 20 UR - http://people.oregonstate.edu/~marshaby/Papers/MCDONALD_BIOINFORMATICS.pdf CP - 18 U2 - a U4 - 648206336 ID - 648206336 ER - TY - HEAR T1 - Genescene: Biomedical text and data mining Y1 - 2003 A1 - Leroy,Gondy A1 - Chen,Hsinchun A1 - Martinez,Jessie A1 - Eggers,S A1 - Falsey,R A1 - Kislin,K A1 - Huang,Zan A1 - Li,Jiexun A1 - Xu,Jennifer A1 - McDonald,Daniel A1 - Ng,Gavin KW - BIS JA - ACM/IEEE Joint Conference on Digital Libraries (JCDL 2003) CY - Houston, TX, USA U2 - c U4 - 98584117248 ID - 98584117248 ER - TY - CONF T1 - Knowledge Management and E-Learning: the GetSmart Experience T2 - Proceedings of the 2003 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2003), May 2003, Houston, Texas Y1 - 2003 A1 - Marshall,Byron A1 - Zhang,Yiwen A1 - Chen,Hsinchun A1 - Lally,Ann A1 - Shen,Rao A1 - Fox,Edward A1 - Cassel,Lillian KW - Accounting KW - BIS AB - 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. JA - Proceedings of the 2003 Joint ACM/IEEE Conference on Digital Libraries (JCDL 2003), May 2003, Houston, Texas UR - http://people.oregonstate.edu/~marshaby/Papers/Marshall_JCDL2003_GetSmart.pdf U2 - b U4 - 2606821377 ID - 2606821377 ER -