This paper develops a new behavioral model of information seeking on the Web by combining theoretical elements from information science and organization science. The model was tested during the first phase of a study of how managers and information technology (IT) specialists use the Web to seek external information as part of their daily work. Participants answered a questionnaire and were interviewed individually in order to understand their information needs and information seeking preferences. A custom-developed tracker application was installed on their workplace computers, or their browsers were redirected through a proxy server set up by the research team. Participants' Web-use activities were then monitored continuously for two work weeks. The tracker application recorded participants' Web browser actions, while the proxy recorded HTTP requests and transfers. In a follow-up round of personal interviews, participants recalled critical incidents of using information from the
tomotopy is a Python extension of tomoto (Topic Modeling Tool) which is a Gibbs-sampling based topic model library written in C++. It utilizes a vectorization of modern CPUs for maximizing speed. The current version of tomoto supports several major topic models including
In natural language understanding, there is a hierarchy of lenses through which we can extract meaning - from words to sentences to paragraphs to documents. At the document level, one of the most useful ways to understand text is by analyzing its topics.
A. Ferraro, M. Ekstrand, и C. Bauer. Proceedings of the 18th ACM Conference on Recommender Systems, стр. 884–889. New York, NY, USA, Association for Computing Machinery, (08.10.2024)