Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Probabilistic and genetic algorithms in document retrieval
Communications of the ACM
Automatic text processing
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Journal of the American Society for Information Science
Information Processing and Management: an International Journal - Special issue: history of information science
Journal of the American Society for Information Science
Exploring the similarity space
ACM SIGIR Forum
Users' criteria for relevance evaluation: a cross-situational comparison
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Making large-scale support vector machine learning practical
Advances in kernel methods
A smart itsy bitsy spider for the web
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
A fuzzy genetic algorithm approach to an adaptive information retrieval agent
Journal of the American Society for Information Science
Applying genetic algorithms to query optimization in document retrieval
Information Processing and Management: an International Journal
Personalization of search engine services for effective retrieval and knowledge management
ICIS '00 Proceedings of the twenty first international conference on Information systems
Machine Learning
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!
Communications of the ACM
Web classification using support vector machine
Proceedings of the 4th international workshop on Web information and data management
A test of genetic algorithms in relevance feedback
Information Processing and Management: an International Journal
The concept of relevance in IR
Journal of the American Society for Information Science and Technology
Ranking Function Optimization for Effective Web Search by Genetic Programming: An Empirical Study
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
IEEE Transactions on Knowledge and Data Engineering
Tuning before feedback: combining ranking discovery and blind feedback for robust retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A generic ranking function discovery framework by genetic programming for information retrieval
Information Processing and Management: an International Journal
Journal of the American Society for Information Science and Technology
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
An integrated two-stage model for intelligent information routing
Decision Support Systems
Genetic Programming-Based Discovery of Ranking Functions for Effective Web Search
Journal of Management Information Systems
Metadata and its impact on libraries: Book Reviews
Journal of the American Society for Information Science and Technology
Population variation in genetic programming
Information Sciences: an International Journal
Directly optimizing evaluation measures in learning to rank
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
An ontology-based approach to learnable focused crawling
Information Sciences: an International Journal
Incorporating domain knowledge into data mining classifiers: An application in indirect lending
Decision Support Systems
Identification of factors predicting clickthrough in Web searching using neural network analysis
Journal of the American Society for Information Science and Technology
Challenges rising from learning motif evaluation functions using genetic programming
Proceedings of the 12th annual conference on Genetic and evolutionary computation
An adaptive learning automata-based ranking function discovery algorithm
Journal of Intelligent Information Systems
An adaptive learning to rank algorithm: Learning automata approach
Decision Support Systems
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Ranking function is instrumental in affecting the performance of a search engine. Designing and optimizing a search engine's ranking function remains a daunting task for computer and information scientists. Recently, genetic programming (GP), a machine learning technique based on evolutionary theory, has shown promise in tackling this very difficult problem. Ranking functions discovered by GP have been found to be significantly better than many of the other existing ranking functions. However, current GP implementations for ranking function discovery are all designed utilizing the Vector Space model in which the same term weighting strategy is applied to all terms in a document. This may not be an ideal representation scheme at the individual query level considering the fact that many query terms should play different roles in the final ranking. In this paper, we propose a novel nonlinear ranking function representation scheme and compare this new design to the well-known Vector Space model. We theoretically show that the new representation scheme subsumes the traditional Vector Space model representation scheme as a special case and hence allows for additional flexibility in term weighting. We test the new representation scheme with the GP-based discovery framework in a personalized search (information routing) context using a TREC web corpus. The experimental results show that the new ranking function representation design outperforms the traditional Vector Space model for GP-based ranking function discovery.