Entity retrieval has received increasing research attention. The recent progress in deep and machine learning techniques provides powerful tools for developing effective entity-centered solutions. This workshop series provides a platform where ...

Entity retrieval has received increasing research attention from both the Information Retrieval (IR) and Semantic Web communities. This workshop series provides a platform where interdisciplinary studies of entity retrieval can be presented, and focused ...

Understanding searchers' queries is an essential component of semantic search systems. In many cases, search queries involve specific attributes of an entity in a knowledge base (KB), which can be further used to find query answers. In this study, we ...

Knowledge Graphs capture the semantic relations between real-world entities and can thus, allow end-users to explore different aspects of an entity of interest by traversing through the edges in the graph. Most of the state-of-the-art methods in entity ...

We introduce the concept of hypercue, a complement to the hyperlink in the form of an interactive representation of real-world entities, e.g. persons, places, concepts, providing personalized access points to information. As a pendant to the hyperlink, ...

Ad-hoc entity search, which is to retrieve a ranked list of relevant entities in response to a query of natural language question, has been widely studied. It has been shown that category matching of entities, especially when matching to fine-grained ...

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 ...

The entity set expansion problem is to expand a small set of seed entities to a more complete set of similar entities. It can be applied in applications such as web search, item recommendation and query expansion. Traditionally, people solve this ...

Identifying the target types of entity-bearing queries can help improve retrieval performance as well as the overall search experience. In this work, we address the problem of automatically detecting the target types of a query with respect to a type ...

The paper introduces an open domain entity search system called ESearch, which aims at finding a list of relevant entities to an open domain entity search query (a natural language question). The system is built on top of a Wikipedia text corpus, as well ...

Surface computing allows flexible search interaction where users can manipulate the representation of entities recommended for them to create new queries or augment existing queries by taking advantage of increased screen estate and almost physical ...

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. ...

Individuals living in highly networked societies publish a large amount of personal, and potentially sensitive, information online. Web investigators can exploit such information for a variety of purposes, such as in background vetting and fraud ...

Web search engines often retrieve answers for queries about popular entities from a growing knowledge base that is populated by a continuous information extraction process. However, less popular entities are not frequently mentioned on the web and are ...

Recently Web search engines have built knowledge graphs to support entity search and to provide structural summaries called \emph{knowledge cards} for entities mentioned in queries. Different knowledge cards might be complementary or even have conflicts ...

Many people seek majority opinions by searching for question-answers that are uploaded by others or uploading their own questions on social media sites. However, people have to read through a large number of documents returned by search services to find ...

To help users cope with the scale and influx of new information, professional social networks (PSNs) provide a search functionality. However, most of the search engines within PSNs today only support keyword queries and basic faceted search capabilities ...

Entity retrieval has seen a lot of interest from the research community over the past decade. Ten years ago, the expertise retrieval task gained popularity in the research community during the TREC Enterprise Track [10]. It has remained relevant ever ...

Entering 'Football Players from United States' when searching for 'American Footballers' is an example of vocabulary mismatch, which occurs when different words are used to express the same concepts. In order to address this phenomenon for entity search ...

Semantic search refers to a broad array of methods that aim to improve retrieval by interpreting queries beyond the traditional weighted bag of words model of document retrieval. In this talk, we will focus on the subset of these methods that rely on ...