The Application of Fuzzy Logic to the Construction of the Ranking Function of Information Retrieval Systems
<|reference_start|>The Application of Fuzzy Logic to the Construction of the Ranking Function of Information Retrieval Systems: The quality of the ranking function is an important factor that determines the quality of the Information Retrieval system. Each document is assigned a score by the ranking function; the score indicates the likelihood of relevance of the document given a query. In the vector space model, the ranking function is defined by a mathematic expression. We propose a fuzzy logic (FL) approach to defining the ranking function. FL provides a convenient way of converting knowledge expressed in a natural language into fuzzy logic rules. The resulting ranking function could be easily viewed, extended, and verified: * if (tf is high) and (idf is high) > (relevance is high); * if (overlap is high) > (relevance is high). By using above FL rules, we are able to achieve performance approximately equal to the state of the art search engine Apache Lucene (deltaP10 +0.92%; deltaMAP -0.1%). The fuzzy logic approach allows combining the logic-based model with the vector model. The resulting model possesses simplicity and formalism of the logic based model, and the flexibility and performance of the vector model.<|reference_end|>
@article{rubens2006the,
    title={The Application of Fuzzy Logic to the Construction of the Ranking
  Function of Information Retrieval Systems},
    author={Neil Rubens},
    journal={N. Rubens. The application of fuzzy logic to the construction of
  the ranking function of information retrieval systems. Computer Modelling and
  New Technologies, 10(1):20-27, 2006},
    year={2006},
    archivePrefix={arXiv},
    eprint={cs/0610039},
    primaryClass={cs.IR cs.AI}
}