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HEEL: exploratory entity linking for heterogeneous information networks

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Abstract

A heterogeneous information network (HIN) is a ubiquitous data model, consisting of multiple types of entities and relations. Names of entities in HINs are inherently ambiguous, making it difficult to fully disambiguate a HIN. In this paper, we introduce the task of exploratory entity linking for HINs. Given a partially disambiguated HIN, we aim at linking ambiguous names to disambiguated entities in the HIN if their referent entities are present. We also try to “explore” other alternatives by discovering new entities and adding them to the HIN. A partial classification EM-based approach is proposed to address this task. We present a constrained probability propagation model to link surface names to entities in the HIN. New entity detection process is modeled as a maximum edge weight clique problem. Experiments illustrate that our method outperforms state-of-the-art methods for entity linking with HINs and author name disambiguation.

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Notes

  1. In meta-path description, we use P, A, T, V and Y to represent any nodes (i.e., entities) in the FDS with the type of paper, author, term, venue and year, respectively.

  2. http://dblp.dagstuhl.de/xml/release/.

  3. https://tartarus.org/martin/PorterStemmer/.

  4. To our knowledge, there exist some other EL methods that consider the NIL issue such as [23]. But their task is to link mentions in the plain texts to entities in the knowledge bases and it is not easy to modify them for EL with HINs.

  5. There are no unlinkable records for the remaining two author names.

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Acknowledgements

This work is supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000904. Chengyu Wang is partially supported by the Outstanding Doctoral Dissertation Cultivation Plan of Action under Grant No. YB2016040.

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Authors and Affiliations

  1. School of Computer Science and Software Engineering, East China Normal University, Shanghai, 200062, China

    Chengyu Wang & Xiaofeng He

  2. School of Data Science and Engineering, East China Normal University, Shanghai, 200062, China

    Aoying Zhou

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  1. Chengyu Wang
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  2. Xiaofeng He
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  3. Aoying Zhou
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Correspondence to Xiaofeng He.

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Wang, C., He, X. & Zhou, A. HEEL: exploratory entity linking for heterogeneous information networks. Knowl Inf Syst 62, 485–506 (2020). https://doi.org/10.1007/s10115-019-01354-1

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