• Automatic Concept Classification of Text From Electronic Meetings

      Chen, Hsinchun; Hsu, P.; Orwig, Richard E.; Hoopes, L.; Nunamaker, Jay F. (ACM, 1994-10)
      In this research we adopted an artificial intelligence (AI) approach to designing an automatic concept classification tool for electronic brainstorming output. The role of AI techniques such as machine learning and neural networks computing in groupware development can be significant. Through extensive content analysis, concept space generation, and neural network-based concept classification, our system can generate a tentative list of the important ideas and topics represented in meeting comments. Participants then can examine the systemâ s suggested list and the underlying comments. They can also revise or augment the list to produce their final consensus list. Allowing the system to act as an â intelligentâ aide for idea organization can alleviate some of the burdens of convergent tasks.
    • A graphical self-organizing approach to classifying electronic meeting output

      Orwig, Richard E.; Chen, Hsinchun; Nunamaker, Jay F. (Wiley Periodicals, Inc, 1997-02)
      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.
    • Information Visualization for Collaborative Computing

      Chen, Hsinchun; Nunamaker, Jay F.; Orwig, Richard E.; Titkova, Olga (IEEE, 1998-08)
      A prototype tool classifies output from an electronic meeting system into a manageable list of concepts, topics, or issues that a group can further evaluate. In an experiment with output from GroupSystems electronic meeting system, the tool's recall ability was comparable to that of a human facilitator, but took roughly a sixth of the time.
    • Internet Categorization and Search: A Self-Organizing Approach

      Chen, Hsinchun; Schuffels, Chris; Orwig, Richard E. (Academic Press, Inc., 1996)
      The problems of information overload and vocabulary differences have become more pressing with the emergence of increasingly popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet WWW software are based on either keyword search (e.g., the Lycos server at CMU, the Yahoo server at Stanford) or hypertext browsing (e.g., Mosaic and Netscape). This research aims to provide an alternative concept-based categorization and search capability for WWW servers based on selected machine learning algorithms. Our proposed approach, which is grounded on automatic textual analysis of Internet documents (homepages), attempts to address the Internet search problem by first categorizing the content of Internet documents. We report results of our recent testing of a multilayered neural network clustering algorithm employing the Kohonen self-organizing feature map to categorize (classify) Internet homepages according to their content. The category hierarchies created could serve to partition the vast Internet services into subject-specific categories and databases and improve Internet keyword searching and/or browsing.
    • Internet Categorization and Search: A Self-Organizing Approach

      Chen, Hsinchun; Schuffels, Chris; Orwig, Richard E. (Academic Press, Inc., 1996)
      The problems of information overload and vocabulary differences have become more pressing with the emergence of increasingly popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet WWW software are based on either keyword search (e.g., the Lycos server at CMU, the Yahoo server at Stanford) or hypertext browsing (e.g., Mosaic and Netscape). This research aims to provide an alternative concept-based categorization and search capability for WWW servers based on selected machine learning algorithms. Our proposed approach, which is grounded on automatic textual analysis of Internet documents (homepages), attempts to address the Internet search problem by first categorizing the content of Internet documents. We report results of our recent testing of a multilayered neural network clustering algorithm employing the Kohonen self-organizing feature map to categorize (classify) Internet homepages according to their content. The category hierarchies created could serve to partition the vast Internet services into subject-specific categories and databases and improve Internet keyword searching and/or browsing.
    • A Multi-Agent View of Strategic Planning Using Group Support Systems and Artificial Intelligence

      Orwig, Richard E.; Chen, Hsinchun; Vogel, D.; Nunamaker, Jay F. (Kluwer, 1996)
      The strategic planning process is dynamic and complex. Including a Group Support System (GSS) in the problem-solving process can improve the content quality of the strategic plan by allowing increased participation by more members of the organization. However, it can also add to the complexity of the problem by increasing the quantity of textual information that can result from group activity. Added complexity increases cognitive overload and frustrations of those participants negotiating the contents of the strategic plan. This article takes a multi-agent view of the strategic planning process. It considers group participants as multiple agents concerned with the content quality of the strategic plan. The facilitator agent is responsible for guiding groups in the strategic plan construction process as well as for solving process problems such as cognitive overload. We introduce an AI Concept Categorizer agent, a software tool that supports the facilitator in addressing the process problem of cognitive overload associated with convergent group activities by synthesizing group textual output into conceptual clusters. The implementation of this tool reduces frustrations which groups encounter in the process of classifying textual output and provides more time for discussion of the concepts themselves. Because of the large amount of convergent activity necessary for strategic planning, the addition of the AI Concept Categorizer to the strategic planning process should increase the quality of the strategic plan and the buy-in of the participants in the strategic planning process.