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.
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
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
A. Ferraro, M. Ekstrand, and C. Bauer. Proceedings of the 18th ACM Conference on Recommender Systems, page 884–889. New York, NY, USA, Association for Computing Machinery, (Oct 8, 2024)