Artificial Intelligence Lab, Department of MIS, University of Arizona / There has been renewed research interest in using the statistical approach to extraction of key phrases from Chinese documents because existing approaches do not allow online frequency updates after phrases have been extracted. This consequently results in inaccurate, partial extraction. In this paper, we present an updateable PAT-tree approach. In our experiment, we compared our approach with that of Lee-Feng Chien with that showed an improvement in recall from 0.19 to 0.43 and in precision from 0.52 to 0.70. This paper also reviews the requirements for a data structure that facilitates implementation of any statistical approaches to key-phrase extraction, including PATtree, PAT-array and suffix array with semi-infinite strings.

Artificial Intelligence Lab, Department of MIS, University of Arizona / This article describes research in the application of a Kohonen Self-Organizing Map (SOM) to the problem of classification of electronic brainstorming output and an evaluation of the results. This research builds upon previous work in automating the meeting classification process using a Hopfield neural network. Evaluation of the Kohonen output comparing it with Hopfield and human expert output using the same set of data found that the Kohonen SOM performed as well as a human expert in representing term association in the meeting output and outperformed the Hopfield neural network algorithm. Recall of consensus meeting concepts and topics using the Kohonen algorithm was equivalent to that of the human expert.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Law enforcement agencies across the United States have begun to focus on innovative knowledge management technologies to aid in the analysis of criminal information. The use of such technologies can serve as intelligence tools to combat criminal activity by aiding in case investigation or even by predicting criminal activity. Funded by the National Institute of Justice, the University of Arizonaâ s Artificial Intelligence Lab has teamed with the Tucson Police Department (TPD) to develop the Coplink Concept Space application, which serves to uncover relationships between different types of information currently existing in TPDâ s records management system. A small-scale field study involving real law enforcement personnel indicates that the use of Coplink Concept Space can reduce the time spent on the investigative task of linking criminal information as well as provide strong arguments for expanded development of similar knowledge management systems in support of law enforcement.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Nanoscale science and engineering (NSE) and related areas have seen rapid growth in recent years. The speed and scope of development in the field have made it essential for researchers to be informed on the progress across different laboratories, companies, industries and countries. In this project, we experimented with several analysis and visualization techniques on NSE-related United States patent documents to support various knowledge tasks. This paper presents results on the basic analysis of nanotechnology patents between 1976 and 2002, content map analysis and citation network analysis. The data have been obtained on individual countries, institutions and technology fields. The top 10 countries with the largest number of nanotechnology patents are the United States, Japan, France, the United Kingdom, Taiwan, Korea, the Netherlands, Switzerland, Italy and Australia. The fastest growth in the last 5 years has been in chemical and pharmaceutical fields, followed by semiconductor devices. The results demonstrate potential of information-based discovery and visualization technologies to capture knowledge regarding nanotechnology performance, transfer of knowledge and trends of development through analyzing the patent documents.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Presentation given by Hsinchun Chen at the NASA Meeting during PMSEP3 on the future of knowledge management. The presentation describes research performed by the Artificial Intelligence Lab at the University of Arizona to create a Perpetual Self-Organizing (PSO) approach to knowledge management funded by NSF, DARPA, NASA, NIJ, and NIH.

For well over a century, the catalog has served libraries and their users as a guide and index to publications collected by an institution. The attributes of the catalog that have made it a valuable resource are desirable traits in any information management tool.The Library catalog user has traditionally assumed that items listed in the catalog were carefully chosen to support an institutional mission and that they were available for her inspection. Internet portals, gateways to the Web, like the catalog, offer access to a wide range of resources, but differ from the catalog in a number of ways, perhaps most significantly in that they facilitate searching and retrieval from a vast, often uncoordinated array of sites, rather than the carefully delimited sphere of the library's collections. Web information has proven much more volatile, ephemeral, and heterogeneous. Can we re-interpret the catalog so that it can serve effectively as a portal to the Internet? Is the catalog the appropriate model for discovery and retrieval of highly dynamic, rapidly multiplying, networked documents? Until relatively recently, the catalog has been the dominant index to published literature for library users. Web portals are rapidly usurping this primacy. Libraries today are struggling as they strain to incorporate a variety of resources in diverse formats in their catalogs and to maintain centrality and relevancy in the digital world. This paper will examine the features of the catalog and their portability to the Web, and will make recommendations about the Library catalog's role in providing access to Internet resources.

No description available.

Artificial Intelligence Lab, Department of MIS, University of Arizona / 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 the information 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.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Much of the work in business and academia is performed by groups of people. While significant advancement has been achieved in enhancing individual productivity by making use of information technology, little has been done to improve group productivity. Prior research suggests that we should know more about individual differences among group members as they respond to technology if we are to develop useful systems that can support group activities. We report results of a cognitive study in which researchers were observed performing three complex information entry and indexing tasks using an Integrated Collaborative Research System. The observations have revealed a taxonomy of knowledge and cognitive processes involved in the indexing and management of information in a research collaboration environment. A detailed comparison of knowledge elements and cognitive processes exhibited by senior researchers and junior researchers has been made in this article. Based on our empirical findings, we have developed a framework to explain the information management process during research collaboration. Directions for improving design of Integrated Collaborative Research Systems are also suggested.

This report investigates the internal knowledge transfer process of consultancy firms on both the organizational and individual levels. Essentially, the creation and application of knowledge yield the key competence for consultancy companies, a large part of which in- volves knowledge transfer. Knowledge transfer is seen as a process of making knowledge available to the organization, allowing others to harvest the full value of it and ultimately creating value for the firm. However, the transfer of knowledge is no simple and linear process; it entails challenges that can impede the process and complicate consultancy com- panies’ daily operations. By being aware of these obstacles, companies can better prepare themselves against them. Therefore, this report seeks to reveal challenges arising on an or- ganizational and individual level for consultancy companies, why they occur and suggest ways to prepare for them. To conduct this study, we have been approaching the topic from a positivist perspective. Two case studies of prominent consultancy companies - KPMG and Grant Thornton - were constructed. The empirical findings were then analyzed and compared to renowned theories in the field: the SECI- model of knowledge conversion by Nonaka & Takeuchi (1991; 1995) and the stage theory of knowledge transfer by Szulanski (1996; 2000). The conclusion of this study is that challenges arising from knowledge transfer in consultancy firms concern individuals and time. Therefore, these two resources should be taken into account at all times.