Corpus ID: 15695468

NTCIR-5 Query Expansion Experiments using Term Dependence Models

@inproceedings{Eguchi2005NTCIR5QE,
  title={NTCIR-5 Query Expansion Experiments using Term Dependence Models},
  author={Koji Eguchi},
  booktitle={NTCIR},
  year={2005}
}
  • K. Eguchi
  • Published in NTCIR 2005
  • Computer Science
This paper reports the results of our experiments performed for the Query Term Expansion Subtask, a subtask of the WEB Task, at the Fifth NTCIR Workshop, and the results of our further experiments. In this paper we mainly investigated: (i) the effectiveness of query formulation by composing or decomposing compound words and phrases of the Japanese language, which is based on a theoretical framework via Markov random fields, but taking into account special features of the Japanese language; and… Expand
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References

SHOWING 1-10 OF 25 REFERENCES
Overview of the Informational Retrieval Task at NTCIR-4 WEB
This paper gives an overview of the Informational Retrieval Task 2 that was conducted from 2003 to 2004 as a subtask of the WEB Task at the Fourth NTCIR Workshop (‘NTCIR-4 WEB’). In the InformationalExpand
Thomson Legal and Regulatory at NTCIR-3: Japanese, Chinese and English Retrieval Experiments
TLDR
This work compared word-based and character-based index- ing, as well as query formulation using characters and character bigrams in Japanese retrieval, and showed that word- based and bigram-based retrieval show similar perfor- mance for most query formulation approaches, while they outperform character- based retrieval. Expand
RICOH at NTCIR-2
TLDR
At NTCIR-2, RICOH submitted eight runs for the Japanese IR task, which features a modi ed version of the Okapi's probabilistic model. Expand
Experiments in Japanese text retrieval and routing using the NEAT system
TLDR
Indexing using dictionary based morphological analysis and character strings are both shown to be individually effective, but marginally better in combination, and relevance feedback can be used effectively for query expansion in Japanese routing applications. Expand
Experiments on Cross-language and Patent Retrieval at NTCIR-3 Workshop
TLDR
An automatic relevance feedback procedure for document ranking formula based on logistic regression, and a procedure for automatically extracting Chinese/Japanese translations of English words from search results returned from Internet search engines using English words as queries are presented. Expand
A Markov random field model for term dependencies
TLDR
A novel approach is developed to train the model that directly maximizes the mean average precision rather than maximizing the likelihood of the training data, and significant improvements are possible by modeling dependencies, especially on the larger web collections. Expand
Overview of the Web Retrieval Task at the Third NTCIR Workshop
This paper gives an overview of the Web Retrieval Task that was conducted from 2001 to 2002 at the Third NTCIR Workshop. In the Web Retrieval Task, we attempted to assess the retrieval effectivenessExpand
Indri at TREC 2004: Terabyte Track
TLDR
An overview of experiments carried out at the TREC 2004 Terabyte Track using the Indri search engine, which is based on the inference network framework and supports structured queries, but unlike INQUERY, it uses language modeling probabilities within the network which allows for added flexibility. Expand
Combining the language model and inference network approaches to retrieval
TLDR
This paper combines the language modeling and inference network approaches into a single framework that allows structured queries to be evaluated using language modeling estimates and reaffirms that high quality structured queries outperform unstructured queries. Expand
The use of phrases and structured queries in information retrieval
TLDR
The results show that using phrases in this way can improve performance, and that phrases that are automatically extracted from a natural language query perform nearly as well as manually selected phrases. Expand
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