Matches in ScholarlyData for { ?s ?p ?o. }
- item-6 type ListItem.
- item-6 hasContent shujie-shang.
- item-6 next item-7.
- item-6 previous item-5.
- item-7 type ListItem.
- item-7 hasContent mingcheng-qu.
- item-7 next item-8.
- item-7 previous item-6.
- item-8 type ListItem.
- item-8 hasContent gang-lu.
- item-8 previous item-7.
- 179 type InProceedings.
- 179 label "Search Result Re-ranking Based on Gap between Search Queries and Social Tags".
- 179 sameAs 179.
- 179 abstract "Both search engine click-through log and social annotation have been utilized as user feedback for search result re-ranking. However, to our best knowledge, no previous study has explored the correlation between these two factors for the task of search result re-ranking. In this paper, we show that the gap between search queries and social tags of the same web page can well reflect its user preference score. Motivated by this observation, we propose a novel algorithm, called Query-Tag-Gap (QTG), to rerank search results for better user satisfaction. Intuitively, on one hand, the search users' intentions are generally described by their queries before they read the search results. On the other hand, the web annotators semantically tag web pages after they read the content of the pages. The difference between users' recognition of the same page before and after they read it is a good reflection of user satisfaction. In this extended abstract, we formally define the query set and tag set of the same page as users' pre- and postknowledge respectively. We empirically show the strong correlation between user satisfaction and user's knowledge gap before and after reading the page. Based on this gap, experiments have shown outstanding performance of our proposed QTG algorithm in search result re-ranking.".
- 179 hasAuthorList authorList.
- 179 isPartOf proceedings.
- 179 keyword "Poster Session".
- 179 title "Search Result Re-ranking Based on Gap between Search Queries and Social Tags".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasItem item-5.
- authorList hasLastItem item-5.
- item-1 type ListItem.
- item-1 hasContent jun-yan.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent ning-liu.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent elaine-qing-chang.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent lei-ji.
- item-4 next item-5.
- item-4 previous item-3.
- item-5 type ListItem.
- item-5 hasContent zheng-chen.
- item-5 previous item-4.
- 18 type InProceedings.
- 18 label "Releasing Search Queries and Clicks Privately".
- 18 sameAs 18.
- 18 abstract "The question of how to publish an anonymized search log was brought to the forefront by a well-intentioned, but privacy-unaware AOL search log release. Since then a series of ad-hoc techniques have been proposed in the literature, though none are known to be provably private. In this paper, we take a major step towards a solution: we show how queries, clicks and their associated perturbed counts can be published in a manner that rigorously preserves privacy. Our algorithm is decidedly simple to state, but non-trivial to analyze. On the opposite side of privacy is the question of whether the data we can safely publish is of any use. Our findings offer a glimmer of hope: we demonstrate that a non-negligible fraction of queries and clicks can indeed be safely published via a collection of experiments on a real search log. In addition, we select an application, keyword generation, and show that the keyword suggestions generated from the perturbed data resemble those generated from the original data.".
- 18 hasAuthorList authorList.
- 18 isPartOf proceedings.
- 18 keyword "Data Mining".
- 18 title "Releasing Search Queries and Clicks Privately".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasLastItem item-4.
- item-1 type ListItem.
- item-1 hasContent aleksandra-korolova.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent krishnaram-kenthapadi.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent nina-mishra.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent alexandros-ntoulas.
- item-4 previous item-3.
- 180 type InProceedings.
- 180 label "Signaling Emotion in Tagclouds".
- 180 sameAs 180.
- 180 abstract "In order to create more attractive tagclouds that get people interested in tagged content, we propose a simple but novel tagcloud where font size is determined by tag's entropy value, not the popularity to its content. Our method raises users' emotional interest in the content by emphasizing more emotional tags. Our initial experiments show that emotional tagclouds attract more attention than normal tagclouds at first look; thus they will enhance the role of tagcloud as a social signaller.".
- 180 hasAuthorList authorList.
- 180 isPartOf proceedings.
- 180 keyword "Poster Session".
- 180 title "Signaling Emotion in Tagclouds".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasLastItem item-4.
- item-1 type ListItem.
- item-1 hasContent takeharu-eda.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent toshio-uchiyama.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent tadasu-uchiyama.
- item-3 next item-4.
- item-3 previous item-2.