Package dragon.ir.search
A package for text retrieval and its evaluation
See:
Description
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Interface Summary |
| Searcher |
Interface of Text Searcher |
Package dragon.ir.search Description
A package for text retrieval and its evaluation
Package Specification
The toolkit provides a well-defined framework for text retrieval. The first step is to generate a query according to the topic descriptions
(such as TREC Topic files). Please refer to the package of dragon.ir.query for query generation. The second step is to create a searcher.
Since there are so many different retrieval models, the toolkit creates an interface called Smoother to hide the implementation details of
different models. Thus, the routine for searching is the same for different models. One can simply call a full rank searcher or a partial
rank searcher. The toolkit has implemented various language model smoothing methods as well as traditional probabilistic and vector space
models. Pseudo-relevance feedback and query expansion are two frequently used techniques for improving the effectiveness of IR. One can call
a feedback searcher or an expansion searcher to incorporate these two techniques, respectively. The details of the feedback approaches and
query expansion approaches are encapsulated into the implantation class of two interfaces, Feedback and Expansion, respectively. To evaluate
the IR performance using TREC protocol, please call dragon.ir.search.evaluate.TrecEva.