THE STATE-OF-THE-ART IN TEXT FILTERING

This paper develops a conceptual framework for text filtering practice and research, and reviews present practice in the field. Text filteri ng is an information seeking process in which documents are selected f rom a dynamic text stream to satisfy a relatively stable and specific information need. A model of the information seeking process is introd uced and specialized to define text Altering. The historical developme nt of text filtering is then reviewed and case studies of recent work are used to highlight important design characteristics of modern text filtering systems. User modeling techniques drawn from information ret rieval, recommender systems, machine learning and other fields are des cribed. The paper concludes with observations on the present state of the art and implications for future research on text filtering.