PAWS meeting - Apr 15, 2009
Jae-wook presenting paper Combining document representations for known item search by Paul Ogilvie and Jamie Callan
The paper investigates the pre-conditions for successful combination of document representations formed from structural markup for the task of known-item search. As this task is very similar to work in meta-search and data fusion, we adapt several hypotheses from those research areas and investigate them in this context. To investigate these hypotheses, we present a mixture-based language model and also examine many of the current meta-search algorithms. We find that compatible output from systems is important for successful combination of document representations. We also demonstrate that combining low performing document representations can improve performance, but not consistently. We find that the techniques best suited for this task are robust to the inclusion of poorly performing document representations. We also explore the role of variance of results across systems and its impact on the performance of fusion, with the surprising result that the correct documents have higher variance across document representations than highly ranking incorrect documents.
Dhruba Baishya presenting a set of innovative visualization techniques, including:
- eigen factor score
- dewey circles
- ny times api
- flickr ecosystem
- ted sphere
- radial social network
- knowledge network
- author co-citation
- euro2004
- web trend map
- los ojos del mundo
- botanical tree
- tagging behavior in nicovideo
- flickr group
Related links
- http://www.visualcomplexity.com/vc/
- http://infosthetics.com/
- http://developer.nytimes.com/visualizations_app/
The paper investigates the pre-conditions for successful combination of document representations formed from structural markup for the task of known-item search. As this task is very similar to work in meta-search and data fusion, we adapt several hypotheses from those research areas and investigate them in this context. To investigate these hypotheses, we present a mixture-based language model and also examine many of the current meta-search algorithms. We find that compatible output from systems is important for successful combination of document representations. We also demonstrate that combining low performing document representations can improve performance, but not consistently. We find that the techniques best suited for this task are robust to the inclusion of poorly performing document representations. We also explore the role of variance of results across systems and its impact on the performance of fusion, with the surprising result that the correct documents have higher variance across document representations than highly ranking incorrect documents.
Dhruba Baishya presenting a set of innovative visualization techniques, including:
- eigen factor score
- dewey circles
- ny times api
- flickr ecosystem
- ted sphere
- radial social network
- knowledge network
- author co-citation
- euro2004
- web trend map
- los ojos del mundo
- botanical tree
- tagging behavior in nicovideo
- flickr group
Related links
- http://www.visualcomplexity.com/vc/
- http://infosthetics.com/
- http://developer.nytimes.com/visualizations_app/
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