• Corpus ID: 2396293

York University at TREC 2005: HARD Track

@inproceedings{Wen2005YorkUA,
  title={York University at TREC 2005: HARD Track},
  author={Miao Wen and Xiangji Huang and Aijun An and Yan Rui Huang},
  booktitle={TREC},
  year={2005}
}
In an IR model, “user”, “query” and “result” are three important components. Traditionally, a query is considered to be independent of the user. IR systems search documents without considering who issues the query and why the query is asked. However, those factors can affect the user’s satisfaction about the result. The information about the user, such as the genre preference of the user, occupation of the user, location of the user, which are normally called personalized information, indicate… 
1 Citations
HARD Track Overview in TREC 2003: High Accuracy Retrieval from Documents
Abstract : The High Accuracy Retrieval from Documents (HARD) track explores methods for improving the accuracy of document retrieval systems. It does so by considering three questions. Can additional

References

SHOWING 1-3 OF 3 REFERENCES
York University at TREC 2004: HARD and Genomics Tracks
TLDR
York University participated in HARD and Genomics tracks this year and used Okapi BSS (basic search system) as the basis, using a new strategy to automatically expand search terms by using relevance feedback and combined retrieval results from dierent fields into the final result.
SMOG Grading - A New Readability Formula.
TLDR
Although this system, SMOG Grading, is laughably simple, it is in fact more valid than previous readability formulas and the rest of this paper is devoted to substantiating that claim.
HARD 2005 Guideline
  • HARD 2005 Guideline