On-the-fly entity-aware query processing in the presence of linkage

Ioannou, Ekaterini; Nejdl, Wolfgang; Niederée, Claudia; Velegrakis, Yannis

doi:10.14778/1920841.1920898

Cited by 66 publications

(42 citation statements)

References 33 publications

(68 reference statements)

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“…To generate the owl:sameAs statements from the tables in Example 2, we extend our set of mappings M with the following mappings (fragment): 8 Observe that this amounts to making the Unique Name Assumption for the objects retrieved by the mappings from one dataset 9 In the special case where there are several datasets that can be mapped to use common URIs, there is no need for linking tables or any of the techniques presented in this paper. We address the more general case, where this is not the case.…”

Section: Example 2 (Categoriesmentioning

confidence: 99%

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Ontology-Based Integration of Cross-Linked Datasets

Calvanese

Giese

Rezk

2015

The Semantic Web - ISWC 2015

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Abstract. In this paper we tackle the problem of answering SPARQL queries over virtually integrated databases. We assume that the entity resolution problem has already been solved and explicit information is available about which records in the different databases refer to the same real world entity. Surprisingly, to the best of our knowledge, there has been no attempt to extend the standard Ontology-Based Data Access (OBDA) setting to take into account these DB links for SPARQL query-answering and consistency checking. This is partly because the OWL built-in owl:sameAs property, the most natural representation of links between data sets, is not included in OWL 2 QL, the de facto ontology language for OBDA. We formally treat several fundamental questions in this context: how links over database identifiers can be represented in terms of owl:sameAs statements, how to recover rewritability of SPARQL into SQL (lost because of owl:sameAs statements), and how to check consistency. Moreover, we investigate how our solution can be made to scale up to large enterprise datasets. We have implemented the approach, and carried out an extensive set of experiments showing its scalability.

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Section: Example 2 (Categoriesmentioning

confidence: 99%

“…When the links are uncertain, query answering then requires the use of probabilistic database methods, as discussed e.g. in [8] for a limited type of queries. Extending these methods to handle arbitrary SPARQL-style queries is not trivial.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Based Integration of Cross-Linked Datasets

Calvanese

Giese

Rezk

2015

The Semantic Web - ISWC 2015

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“…Ioannou et al [14] on the other hand propose an approach that provides entity resolution in real-time, and works on dynamic databases. Their method is based on using links between the entities in a database combined with a probabilistic database for resolving entities.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Similarity-Aware Inverted Indexing for Real-Time Entity Resolution

Ramadan

Christen

Liang

et al. 2013

Lecture Notes in Computer Science

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Abstract. Entity resolution is the process of identifying groups of records in a single or multiple data sources that represent the same real-world entity. It is an important tool in data de-duplication, in linking records across databases, and in matching query records against a database of existing entities. Most existing entity resolution techniques complete the resolution process offline and on static databases. However, real-world databases are often dynamic, and increasingly organizations need to resolve entities in real-time. Thus, there is a need for new techniques that facilitate working with dynamic databases in real-time. In this paper, we propose a dynamic similarity-aware inverted indexing technique (DySimII) that meets these requirements. We also propose a frequencyfiltered indexing technique where only the most frequent attribute values are indexed. We experimentally evaluate our techniques on a large realworld voter database. The results show that when the index size grows no appreciable increase is found in the average record insertion time (around 0.1 msec) and in the average query time (less than 0.1 sec). We also find that applying the frequency-filtered approach reduces the index size with only a slight drop in recall.

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“…Hence, they require access to the full datasets, while our approach only uses data retrieved for a given search query. The aspect of query-time data integration has been studied for schema alignment during Web data search [11], to identify and consolidate records helpful to process a database query [25], and in the context of probabilistic databases [26].…”

Section: Related Workmentioning

confidence: 99%

Federated Entity Search Using On-the-Fly Consolidation

Herzig

Mika

Blanco

et al. 2013

Lecture Notes in Computer Science

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Abstract. Nowadays, search on the Web goes beyond the retrieval of textual Web sites and increasingly takes advantage of the growing amount of structured data. Of particular interest is entity search, where the units of retrieval are structured entities instead of textual documents. These entities reside in different sources, which may provide only limited information about their content and are therefore called "uncooperative". Further, these sources capture complementary but also redundant information about entities. In this environment of uncooperative data sources, we study the problem of federated entity search, where redundant information about entities is reduced on-the-fly through entity consolidation performed at query time. We propose a novel method for entity consolidation that is based on using language models and completely unsupervised, hence more suitable for this on-the-fly uncooperative setting than state-of-the-art methods that require training data. Further, we apply the same language model technique to deal with the federated search problem of ranking results returned from different sources. Particular novel are the mechanisms we propose to incorporate consolidation results into this ranking. We perform experiments using real Web queries and data sources. Our experiments show that our approach for federated entity search with on-the-fly consolidation improves upon the performance of a state-of-the-art preference aggregation baseline and also benefits from consolidation.

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On-the-fly entity-aware query processing in the presence of linkage

Cited by 66 publications

References 33 publications

Ontology-Based Integration of Cross-Linked Datasets

Ontology-Based Integration of Cross-Linked Datasets

Dynamic Similarity-Aware Inverted Indexing for Real-Time Entity Resolution

Federated Entity Search Using On-the-Fly Consolidation

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