@inproceedings{baezayates2007extracting,
  abstract = {In this paper we study a large query log of more than twenty million queries with the goal of extracting the semantic relations that are implicitly captured in the actions of users submitting queries and clicking answers. Previous query log analyses were mostly done with just the queries and not the actions that followed after them. We first propose a novel way to represent queries in a vector space based on a graph derived from the query-click bipartite graph. We then analyze the graph produced by our query log, showing that it is less sparse than previous results suggested, and that almost all the measures of these graphs follow power laws, shedding some light on the searching user behavior as well as on the distribution of topics that people want in the Web. The representation we introduce allows to infer interesting semantic relationships between queries. Second, we provide an experimental analysis on the quality of these relations, showing that most of them are relevant. Finally we sketch an application that detects multitopical URLs.},
  address = {New York, NY, USA},
  author = {Baeza-Yates, Ricardo and Tiberi, Alessandro},
  booktitle = {KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining},
  doi = {http://doi.acm.org/10.1145/1281192.1281204},
  file = {baezayates2007extracting.pdf:baezayates2007extracting.pdf:PDF},
  groups = {public},
  interhash = {26ca034be705abaf072835784f53d877},
  intrahash = {6e45b65feffd1545c6dca62bf4b8f53d},
  isbn = {978-1-59593-609-7},
  location = {San Jose, California, USA},
  pages = {76--85},
  publisher = {ACM},
  timestamp = {2009-06-01 15:31:03},
  title = {Extracting semantic relations from query logs},
  url = {http://portal.acm.org/citation.cfm?id=1281192.1281204},
  username = {dbenz},
  year = 2007
}

@inproceedings{benz2008analyzing,
  abstract = {The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.},
  author = {Benz, Dominik and Grobelnik, Marko and Hotho, Andreas and Jäschke, Robert and Mladenic, Dunja and Servedio, Vito D. P. and Sizov, Sergej and Szomszor, Martin},
  booktitle = {Proceedings of the Dagstuhl Seminar on Social Web Communities},
  editor = {Alani, Harith and Staab, Steffen and Stumme, Gerd},
  file = {benz2008analyzing.pdf:benz2008analyzing.pdf:PDF},
  groups = {public},
  interhash = {d738d9d90c1c466ee0a73ac0cc3dc4c1},
  intrahash = {6918e578527dec96abb5718f105d9f78},
  issn = {1862-4405},
  number = 08391,
  timestamp = {2009-10-01 18:35:30},
  title = {Analyzing Tag Semantics Across Collaborative Tagging Systems},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2008analyzing.pdf},
  username = {dbenz},
  year = 2008
}