Search Results

The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from a natural language text, and possibly linking them to proper matches in Knowledge Graphs (KGs). Considering Wikidata ...

The task of identifying pieces of evidence in texts is of fundamental importance in supporting qualitative studies in various domains, especially in the humanities. In this paper, we coin the expression themed evidence, to refer to (direct or indirect) ...

Textbooks are educational documents created, structured and formatted in a way that facilitates understanding. Most digital textbooks are released as mere digital copies of their printed counterparts. We present a mechanism that extracts knowledge ...

In story or character driven games, in-game stories are usually manually authored in advance. As the complexity of interactions in games increases, the quantity of hand-crafted text typically follows. Designing stories and composing content by hand is a ...

Navigating large knowledge bases made of billions of triples is very challenging. In this demonstration, we showcase Fouilla, a topical Knowledge Base browser that offers a seamless navigational experience of DBpedia. We propose an original approach ...

Query expansion (QE) is an important process in information retrieval applications that improves the user query and helps in retrieving relevant results. In this paper, we introduce a hybrid query expansion model (HQE) that investigates how ...

In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality ...

In this demo, we introduce the DBpedia chatbot, a knowledge-graph-driven chatbot designed to optimize community interaction. The bot was designed for integration into community software to facilitate the answering of recurrent questions. Four main ...

The DBpedia-entity collection has been used as a standard test collection for entity search in recent years. We develop and release a new version of this test collection, DBpedia-Entity v2, which uses a more recent DBpedia dump and a unified candidate ...

This work investigates the effectiveness of learning to rank methods for entity search. Entities are represented by multi-field documents constructed from their RDF triples, and field-based text similarity features are extracted for query-entity pairs. ...

We deal with the problem of document representation for the task of measuring semantic relatedness between documents. A document is represented as a compact concept graph where nodes represent concepts extracted from the document through references to ...

Queryable Linked Data is published through several interfaces, including sparql endpoints and Linked Data documents. In October 2014, the dbpedia Association announced an official Triple Pattern Fragments interface to its popular dbpedia dataset. ...

Recommendation System has been developed with the growth of Word Wide Web. Recently, Web3.0 or Semantic Web has changed the traditional way of its related approaches, by leveraging knowledge of Linked Open data Cloud which consist of domain specific and ...

The constantly growing amount of Linked Open Data (LOD) datasets constitutes the need for rich metadata descriptions, enabling users to discover, understand and process the available data. This metadata is often created, maintained and stored in diverse ...

It is crucial to enable regular users to explore RDF-compliant data bases in an effective way, regardless their knowledge about the SPARQL or the underlying ontology. Natural language querying have been proposed to address this issue. However it has ...

Linked Open Data (LOD) comprises an unprecedented volume of structured data on the Web. However, these datasets are of varying quality ranging from extensively curated datasets to crowdsourced or extracted data of often relatively low quality. We ...

We propose a graph-based semantic model for representing document content. Our method relies on the use of a semantic network, namely the DBpedia knowledge base, for acquiring fine-grained information about entities and their semantic relations, thus ...

We present a knowledge-rich approach to Web search result clustering which exploits the output of an open-domain entity linker, as well as the types and topical concepts encoded within a wide-coverage ontology. Our results indicate that, thanks to an ...

The advent of the Linked Open Data (LOD) initiative gave birth to a variety of open knowledge bases freely accessible on the Web. They provide a valuable source of information that can improve conventional recommender systems, if properly exploited. In ...

We develop and make publicly available an entity search test collection based on the DBpedia knowledge base. This includes a large number of queries and corresponding relevance judgments from previous benchmarking campaigns, covering a broad range of ...