TY - CONF AU - Krause, Beate AU - Jäschke, Robert AU - Hotho, Andreas AU - Stumme, Gerd A2 - T1 - Logsonomy - Social Information Retrieval with Logdata T2 - HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia PB - ACM CY - New York, NY, USA PY - 2008/ M2 - VL - IS - SP - 157 EP - 166 UR - http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia M3 - http://doi.acm.org/10.1145/1379092.1379123 KW - 2008 KW - analysis KW - engine KW - information KW - l3s KW - logsonomy KW - myown KW - networks KW - retrieval KW - search KW - social KW - wp5 L1 - SN - 978-1-59593-985-2 N1 - N1 - AB - Social bookmarking systems constitute an established

part of the Web 2.0. In such systems

users describe bookmarks by keywords

called tags. The structure behind these social

systems, called folksonomies, can be viewed

as a tripartite hypergraph of user, tag and resource

nodes. This underlying network shows

specific structural properties that explain its

growth and the possibility of serendipitous

exploration.

Today’s search engines represent the gateway

to retrieve information from the World Wide

Web. Short queries typically consisting of

two to three words describe a user’s information

need. In response to the displayed

results of the search engine, users click on

the links of the result page as they expect

the answer to be of relevance.

This clickdata can be represented as a folksonomy

in which queries are descriptions of

clicked URLs. The resulting network structure,

which we will term logsonomy is very

similar to the one of folksonomies. In order

to find out about its properties, we analyze

the topological characteristics of the tripartite

hypergraph of queries, users and bookmarks

on a large snapshot of del.icio.us and

on query logs of two large search engines.

All of the three datasets show small world

properties. The tagging behavior of users,

which is explained by preferential attachment

of the tags in social bookmark systems, is

reflected in the distribution of single query

words in search engines. We can conclude

that the clicking behaviour of search engine

users based on the displayed search results

and the tagging behaviour of social bookmarking

users is driven by similar dynamics. ER -