Informatologia, Vol. 52 No. 3-4, 2019.
Preliminary communication
https://doi.org/10.32914/i.52.3-4.5
SURVEY ON ENTITY LINKING FOR DOMAIN SPECIFIC WITH HETEROGENEOUS INFORMATION NETWORKS
S. Mythrei
; Department of Computer Science and Engineering, PSR Engineering College, Sivakasi, India
S. Singaravelan
; Department of Computer Science and Engineering, PSR Engineering College, Sivakasi, India
Abstract
Entity linking is a task of extracting information that links the mentioned entity in a collection of text with their similar knowledge base as well as it is the task of allocating unique identity to various entities such as locations, individuals and companies. Knowledgebase (KB) is used to optimize the information collection, organization and for retrieval of information. Heterogeneous information networks (HIN) comprises multiple-type interlinked objects with various types of relationship which are becoming increasingly most popular named bibliographic networks, social media networks as well including the typical relational database data. In HIN, there are various data objects are interconnected through various relations. The entity linkage determines the corresponding entities from unstructured web text, in the existing HIN. This work is the most important and it is the most challenge because of ambiguity and existing limited knowledge. Some HIN could be considered as a domain-specific KB. The current Entity Linking (EL) systems aimed towards corpora which contain heterogeneous as web information and it performs sub-optimally on the domain-specific corpora. The EL systems used one or more general or specific domains of linking such as DBpedia, Wikipedia, Freebase, IMDB, YAGO, Wordnet and MKB. This paper presents a survey on domain-specific entity linking with HIN. This survey describes with a deep understanding of HIN, which includes datasets,types and examples with related concepts.
Keywords
Heterogeneous information network; Entity linking; Meta path or structure; Domain-specific; Web Links
Hrčak ID:
234829
URI
Publication date:
30.12.2019.
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