32552978
A Knowledge-Based Design for Hypertext-Based Document Retrieval Systems
This paper presents some aspects of an ongoing research that. aims at incorporating knowledge-based search mechanisms into hypertext-based document retrieval systems. We propose an information structure that is grounded on a semantic network-based thesaurus. It serves to represent the documents and concepts (terms) involved in information retrieval. The second important component of our design is heuristics-based search mechanisms that were derived from our prior cognitive modeling study (which investigated the search strategies of expert searchers). By incorporating these components into a navigation-based hypertext, we attempt to create a system that facilitates effective and efficient information retrieval in a complex retrieval environment.
21266732
User Misconceptions of Information Retrieval Systems
In this paper, we report results of an investigation where thirty subjects were observedperforming subject-based search in an online catalog system. The observationshave revealed a range of misconceptions users have when performing subject-basedsearch. We have developed a taxonomy that characterizes these misconceptions andhypotheses about the causes of the misconceptions. Directions for improving searchperformance are also suggested.
19452291
Cross-Jurisdictional Activity Networks to Support Criminal Investigations
Border and transportation security is a critical part of the Department of Homeland Security's (DHS) national strategy. DHS strategy calls for the creation of "smart borders" where information from local, state, federal, and international sources can be combined to support risk-based management tools for border-management agencies. Sharing cross-jurisdictional law enforcement data is important because criminals take advantage of the fact that information sharing between law enforcement jurisdictions is very limited. Challenges to information integration in this important domain include policy and privacy concerns, data security requirements, semantic or schema-level matching of legacy system data, and identity matching. The BorderSafe project leverages the skills and experiences of a diverse group of researchers, law enforcement officials, and government agencies to address data sharing needs in the Southwest United States. Our demo presents a framework for combining law enforcement data across jurisdictions to support criminal investigation and describes how that framework was used in combining three large, overlapping datasets to produce an integrated system for visualizing criminal activity networks.
35410760
Collaborative Workflow Management for Interagency Crime Analysis
To strengthen homeland security, there is a critical need for new tools that can facilitate real time collaboration among various law enforcement agencies. Through a field study, we find that law enforcement work is knowledge intensive and involves complex collaborative processes interrelating a large number of disparate units in a loosely defined virtual organization. To support knowledge intensive collaboration, we propose a new workflow centric framework to seamlessly integrate previously separate techniques from the fields of information retrieval and workflow management. Specifically, we develop a collaborative workflow management framework for interagency crime analysis. The key contribution of our research is that by integrating various state-of-the-art techniques innovatively, the proposed system can support real time collaboration processes in a virtual organization that evolves dynamically.
38977435
Sharing and Visualizing Infectious Disease Datasets Using the WNV-BOT Portal System
Infectious disease outbreaks are critical threats to public health and national security. Information systems play a central role in developing an effective comprehensive approach to prevent, detect, respond to, and manage infectious disease outbreaks of plants, animals, and humans.
40127439
Authorship Analysis in Cybercrime Investigation
Criminals have been using the Internet to distribute a wide range of illegal materials globally in an anonymous manner, making criminal identity tracing difficult in the cybercrime investigation process. In this study we propose to adopt the authorship analysis framework to automatically trace identities of cyber criminals through messages they post on the Internet. Under this framework, three types of message features, including style markers, structural features, and content-specific features, are extracted and inductive learning algorithms are used to build feature-based models to identify authorship of illegal messages. To evaluate the effectiveness of this framework, we conducted an experimental study on data sets of English and Chinese email and online newsgroup messages. We experimented with all three types of message features and three inductive learning algorithms. The results indicate that the proposed approach can discover real identities of authors of both English and Chinese Internet messages with relatively high accuracies.
37302257
On Maximum Symmetric Subgraphs
Let G be an n-node graph. We address the problem of computing a maximum symmetric graph H from G by deleting nodes, deleting dges, and contracting edges. This NP-complete problem arises naturally from the objective of drawing G as symmetrically as possible. We show that its tractability for the special cases of G being a plane graph, an ordered tree, and an unordered tree, depends on the type of operations used to obtain H from G. Moreover, we give an O(log n)-approximation algorithm for the intractable case that H is obtained from a tree G by contracting edges. As a by-product, we give an O(log n)-approximation algorithm for an NP-complete edit-distance problem.
26701472
Interface descriptions for enterprise architecture
This paper describes our experiences in implementing a repository-based system that records and manages architectural information for an organization-wide set of enterprise information systems. The system is called Interface Descriptions for Enterprise Architecture (IDEA). The IDEA system business case and system creation are discussed, and the use of the system is exemplified by applying it to a set of information systems within a large corporation. We show how the existence of a managed enterprise architecture description enables an important set of analyses: risk analyses, architecture analyses, and change management analyses. Finally, we discuss how the IDEA system has the potential to catalyze even more profound change by changing how the various systems' stakeholders interact.
1463101
RDF/RDFS-based Relational Database Integration
We study the problem of answering queries through a RDF/RDFS ontology, given a set of view-based mappings between one or more relational schemas and this target ontology. Particularly, we consider a set of RDFS semantic constraints such as rdfs:subClassof, rdfs:subPropertyof, rdfs:domain, and rdfs:range, which are present in RDF model but neither XML nor relational models. We formally define the query semantics in such an integration scenario, and design a novel query rewriting algorithm to implement the semantics. On our approach, we highlight the important role played by RDF Blank Node in representing incomplete semantics of relational data. A set of semantic tools supporting relational data integration by RDF are also introduced. The approach have been used to integrate 70 relational databases at China Academy of Traditional Chinese Medicine.
14165227
Special issue: "Web retrieval and mining"
41702110
An analysis of image retrieval tasks in the field of art history
This project applied Jorgensen's three image retrieval tasks (1995) and Enser's four models of image retrieval (1995) to investigate end-users' image retrieval tasks and image query modes in the field of art history. Twenty-six undergraduate students majoring in art history were recruited in this study. They were required to finish a term paper including at least 20 images. The participants' image retrieval tasks were collected by pre- and post-search questionnaires, and a post-search interview. There was a significant difference between the mean number of search keywords or phrases participants planned to use and the mean number of search keywords or phrases they actually used. The study found a significant relationship between the level of success for the search results and the percentage of search keywords or phrases drawn from the topic title or topic description participants planned to use. Implications for image indexing tools and image retrieval system design are proposed.