Isak Taksa

Isak Taksa is an Associate Professor in the Department of Computer Information Systems at Baruch College of the City University of New York (CUNY). His primary research interests include information retrieval, knowledge discovery and text and data mining. He has published extensively on theoretical and applied aspects of Information Retrieval and Search Engine technology in journals including Information Retrieval, Journal of the American Society for Information Science.

Publications

Machine Learning Approach to Search Query Classification
Machine Learning Approach to Search Query Classification
Isak Taksa, Sarah Zelikovitz, Amanda Spink. © 2012. 16 pages.
Search query classification is a necessary step for a number of information retrieval tasks. This chapter presents an approach to non-hierarchical classification of search...
Non-Topical Classification of Query Logs Using Background Knowledge
Non-Topical Classification of Query Logs Using Background Knowledge
Isak Taksa, Sarah Zelikovitz, Amanda Spink. © 2012. 18 pages.
Background knowledge has been actively investigated as a possible means to improve performance of machine learning algorithms. Research has shown that background knowledge plays...
Temporal and Contextual Evaluation of Background Knowledge Discovery for Short Text Classification
Temporal and Contextual Evaluation of Background Knowledge Discovery for Short Text Classification
Isak Taksa, Sarah Zelikovitz, Amanda Spink. © 2012. 20 pages.
Background Knowledge (BK) plays an essential role in machine learning for short-text and non-topical classification. In this paper the authors present and evaluate two...
Non-Topical Classification of Query Logs Using Background Knowledge
Non-Topical Classification of Query Logs Using Background Knowledge
Isak Taksa, Sarah Zelikovitz, Amanda Spink. © 2011. 19 pages.
Background knowledge has been actively investigated as a possible means to improve performance of machine learning algorithms. Research has shown that background knowledge plays...
Handbook of Research on Web Log Analysis
Handbook of Research on Web Log Analysis
Bernard J. Jansen, Amanda Spink, Isak Taksa. © 2009. 628 pages.
Whether searching, shopping, or socializing, Web users leave behind a great deal of data revealing their information needs, mindset, and approaches used, creating vast...
Research and Methodological Foundations of Transaction Log Analysis
Research and Methodological Foundations of Transaction Log Analysis
Bernard J. Jansen, Isak Taksa, Amanda Spink. © 2009. 16 pages.
This chapter outlines and discusses theoretical and methodological foundations for transaction log analysis. We first address the fundamentals of transaction log analysis from a...
Machine Learning Approach to Search Query Classification
Machine Learning Approach to Search Query Classification
Isak Taksa, Sarah Zelikovitz, Amanda Spink. © 2009. 16 pages.
Search query classification is a necessary step for a number of information retrieval tasks. This chapter presents an approach to non-hierarchical classification of search...
Web Log Analysis: Diversity of Research Methodologies
Web Log Analysis: Diversity of Research Methodologies
Isak Taksa, Amanda Spink, Bernard J. Jansen. © 2009. 17 pages.
Web log analysis is an innovative and unique field constantly formed and changed by the convergence of various emerging Web technologies. Due to its interdisciplinary character...