A test collection for entity search in DBpedia

Balog, Krisztian; Neumayer, Robert

doi:10.1145/2484028.2484165

Cited by 52 publications

(49 citation statements)

References 20 publications

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“…The first, ESQ, is a set of 485 entitycentric queries compiled by Balog & Neumayer [4]. We remove from this dataset SemSearch ES and INEX LD queries as they do not fit our setting.…”

Section: Benchmarksmentioning

confidence: 99%

Relationship Queries on Extended Knowledge Graphs

Yahya

Barbosa

Berberich

et al. 2016

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

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Entity search over text corpora is not geared for relationship queries where answers are tuples of related entities and where a query often requires joining cues from multiple documents. With large knowledge graphs, structured querying on their relational facts is an alternative, but often suffers from poor recall because of mismatches between user queries and the knowledge graph or because of weakly populated relations.This paper presents the TriniT search engine for querying and ranking on extended knowledge graphs that combine relational facts with textual web contents. Our query language is designed on the paradigm of SPO triple patterns, but is more expressive, supporting textual phrases for each of the SPO arguments. We present a model for automatic query relaxation to compensate for mismatches between the data and a user's query. Query answers -tuples of entities -are ranked by a statistical language model. We present experiments with different benchmarks, including complex relationship queries, over a combination of the Yago knowledge graph and the entity-annotated ClueWeb'09 corpus.

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“…The first, ESQ, is a set of 485 entitycentric queries compiled by Balog & Neumayer [4]. We remove from this dataset SemSearch ES and INEX LD queries as they do not fit our setting.…”

Section: Benchmarksmentioning

confidence: 99%

Relationship Queries on Extended Knowledge Graphs

Yahya

Barbosa

Berberich

et al. 2016

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

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“…Issues related to some of these aspects have been discussed in the JIWES workshop, first held in 2012, which focused on challenges and tasks in entity search (Balog et al, 2012). To address some of these issues, Balog and Neumayer (2013) released an entity search test collection featuring DBpedia as a dataset together with a large number of queries and relevance judgments from previous evaluation campaigns. With regards to queries, the authors tried to provide a representative set of information needs with varying length, type, origin and complexity.…”

Section: Queriesmentioning

confidence: 99%

An overview of semantic search evaluation initiatives

Elbedweihy

Wrigley

Clough

et al. 2015

Journal of Web Semantics

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“…In the past decade, large-scale public knowledge bases have emerged, such as DBpedia [3], Freebase [2] and Wikidata [4]. These knowledge bases provide a well-structured knowledge representation and have become one of the most popular resources for many applications, such as web search and question answering.…”

Section: Introductionmentioning

confidence: 99%

Explore Entity Embedding Effectiveness in Entity Retrieval

Liu

Xiong

Sun

et al. 2019

Lecture Notes in Computer Science

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This paper explores entity embedding effectiveness in ad-hoc entity retrieval, which introduces distributed representation of entities into entity retrieval. The knowledge graph contains lots of knowledge and models entity semantic relations with the well-formed structural representation. Entity embedding learns lots of semantic information from the knowledge graph and represents entities with a low-dimensional representation, which provides an opportunity to establish interactions between query related entities and candidate entities for entity retrieval. Our experiments demonstrate the effectiveness of entity embedding based model, which achieves more than 5% improvement than the previous state-of-the-art learning to rank based entity retrieval model. Our further analysis reveals that the entity semantic match feature effective, especially for the scenario which needs more semantic understanding.

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A test collection for entity search in DBpedia

Cited by 52 publications

References 20 publications

Relationship Queries on Extended Knowledge Graphs

Relationship Queries on Extended Knowledge Graphs

An overview of semantic search evaluation initiatives

Explore Entity Embedding Effectiveness in Entity Retrieval

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