Name
Abstract | ||
|---|---|---|
In the recent years, the Web has been changing more and more towards the so-called Social Semantic Web. Rather than being based on the link structure between Web pages, the ranking of search results in the Social Semantic Web needs to be based on something new. We believe that it can be based on ontological background knowledge and on user preferences. In this paper, we thus propose an extension of the Datalog+/- ontology language that allows for dealing with partially ordered preferences of groups of users. We focus on answering k-rank queries in this context. In detail, we present different strategies to compute group preferences as an aggregation of the preferences of a collection of single users. We then provide algorithms to answer k-rank queries for DAQs (disjunctions of atomic queries) under these group preferences. We show that such DAQ answering in Datalog+/- can be done in polynomial time in the data complexity, as long as query answering can also be done in polynomial time (in the data complexity) in the underlying classical ontology. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-40381-1_28 | Lecture Notes in Artificial Intelligence |
Field | DocType | Volume |
Ontology (information science),Ontology,Web page,Ranking,Information retrieval,Computer science,Artificial intelligence,Social Semantic Web,Time complexity,Datalog,Machine learning,Ontology language | Conference | 8078 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
14 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Lukasiewicz | 1 | 2618 | 165.18 |
| Maria Vanina Martinez | 2 | 259 | 26.19 |
| Gerardo I. Simari | 3 | 367 | 40.41 |
| Oana Tifrea-Marciuska | 4 | 10 | 4.21 |