traditional email, which enables the user to define and execute ad-hoc

workflows in an intuitive way. This model paves the way for semantic

annotation of implicit, well-defined workflows, thus making them explicit and

exposing the missing information in a machine processable way. Grounding

this work within the Social Semantic Desktop [1] via appropriate ontologies

means that this information can be exploited for the benefit of the user. This

will have a direct impact on their personal information management - given

email is not just a major channel of data exchange between desktops, but it also

serves as a virtual working environment where people collaborate. Thus the

presented workflow model will have a concrete manifestation in the creation,

organization and exchange of semantic desktop data.

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.

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.