Ontology-based personalized search and browsing

By Susan Gauch, J. Chaffee, Alexander Pretschner. Web Intelligence and Agent Systems, 2003

496 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9311ccb1ea835be4ce8b4ae21692fedd878a1b1d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Web search personalization with ontological user profiles (2007, methodology): “Our research follows recent ontology-based personalized search approaches [10, 22] in utilizing the Open Directory Project (ODP)(2) taxonomy as the Web topic ontology.”
An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval (2007, unknown): “One way to view a semantic search engine is as a tool that gets formal ontology-based queries (e.g., in RDQL [32], RQL [19], SPARQL [29], etc.) from a client, executes them against a knowledge base (KB), and returns tuples of ontology values that satisfy the query [3], [4], [6], [24].”
Personalizing search via automated analysis of interests and activities (2005, unknown): “Many commercial information filtering systems use this approach, and it has been explored before to personalize Web search results by Gauch et al. [ 6 ][22].”
An Ontology-Based Information Retrieval Model (2005, methodology): “In the former case, ontologies provide a shallow representation of the information space, equivalent in essence to the taxonomies and thesauri used before the Semantic Web was envisioned [3,6,7,15].”
Measuring personalization of web search (2013, background): “s (e.g., disambiguation of similar search terms, and retrieval of locally relevant results). In fact, the bene˙ts of such personalized rankings has been extensively studied in the research literature [15, 17, 30, 50]. Unfortunately, while the bene˙ts of personalization are well-studied, the potentia”