Semantic Preference Retrieval for Querying Knowledge Bases


This work deals with the problem of automatically creating semantic queries for knowledge bases from preference feedback. Semantic knowledge bases are a good source for retrieving entities for item recommendation. We show that preference decisions are not only based on entities, but also on their corresponding predicate-object relations. By extracting the weights from trained preference models, the weighted predicate-object relations can be stored to a user model. The objective is to use such prototype entities in a general user model to formulate semantic queries for recommendation retrieval.

 author = {Scheel, Christian and Said, Alan and Albayrak, Sahin},
 title = {Semantic preference retrieval for querying knowledge bases},
 booktitle = {Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search},
 series = {JIWES '12},
 year = {2012},
 isbn = {978-1-4503-1601-9},
 location = {Portland, Oregon},
 pages = {6:1--6:6},
 articleno = {6},
 numpages = {6},
 url = {},
 doi = {10.1145/2379307.2379313},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {preference model, semantic query},
Christian Scheel, Alan Said, Sahin Albayrak
1st Joint International Workshop on Entity-oriented and Semantic Search (JIWES) 2012 at the 35th ACM SIGIR Conference