- Language modeling approaches to blog post and feed finding
- The Sixteenth Text REtrieval Conference (TREC 2007), Gaithersburg, MD
- Book/source title
- The Sixteenth Text REtrieval Conference Proceedings (TREC 2007)
- Pages (from-to)
- National Institute of Standards and Technology (NIST)
- Document type
- Conference contribution
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
We describe our participation in the TREC 2007 Blog track. In the opinion task we looked at the differences in performance between Indri and our mixture model, the influence of external expansion and document priors to improve opinion finding; results show that an out-of-the-box Indri implementation outperforms our mixture model, and that external expansion on a news corpus is very benificial. Opinion finding can be improved using either lexicons or the number of comments as document priors.
Our approach to the feed distillation task is based on aggregating post-level scores to obtain a feed-level ranking. We integrated time-based and persistence aspects into the retrieval model. After correcting bugs in our post-score aggregation module we found that time-based retrieval improves results only marginally, while persistence-based ranking results in substantial improvements under the right circumstances.
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