Personal Research Knowledge Graphs

Chakraborty, Prantika; Dutta, Sudakshina; Sanyal, Debarshi Kumar

doi:10.1145/3487553.3524654

Cited by 9 publications

(9 citation statements)

References 22 publications

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“…A personal research knowledge graph (PRKG) can be used to simplify the daily tasks of a researcher (Chakraborty et al, 2022). A PRKG contains structured information about the research‐related activities of a researcher.…”

Section: Application Domains Of Pkgmentioning

confidence: 99%

“…Chakraborty et al (2022) advocate several ways to populate a PRKG (PKG for researchers); these include consensual tracking of the user utterances during research meetings, consensual mining of user emails, actively enquiring the researchers for salient information, and carrying out named entity recognition on research papers.…”

Section: Construction Of Pkgmentioning

confidence: 99%

“…A PKG based on even a sparse user profile can highly personalize the recommendations for books (Torbati et al, 2020) that might interest them. The PRKG (Chakraborty et al, 2022) recommends upcoming conferences for a researcher based on their research interests whereas another PKG (Yang et al, 2022) recommends movies and actors that the user might be interested in.…”

Section: Applications Of Pkgmentioning

confidence: 99%

“…In order to broaden the scope of utilization, PKGs can be linked to public KGs. For example, PKGs handling lifelogs and memories of users (Yen et al, 2021) may connect to social network graphs, while PKGs handling scholarly data (Chakraborty et al, 2022) may connect to a scholarly KG like ORKG, as shown in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

“…(a) Personal knowledge graph based on lifelogs (Yen et al, 2021). (b) Personal research knowledge graph for researchers and academicians (Chakraborty et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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A comprehensive survey of personal knowledge graphs

Chakraborty

Sanyal

2023

WIREs Data Min & Knowl

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Information that can encapsulate a person's daily life and its different aspects provides insightful knowledge. This knowledge can prove to be more useful than general knowledge for improving personalized tasks. When it comes to storing such knowledge, personal knowledge graphs (PKGs) come in as handy saviors. PKGs are knowledge graphs which store details that are pertinent to a user but not, in general, useful to the rest of humanity. Conversational agents can access these PKGs to answer queries related to the user's day‐to‐day life, whereas recommender systems can harness the knowledge stored in PKGs to make personalized suggestions. Despite the immense applicability of PKGs, there has not been significant research in this area. We present an extensive review of PKGs. We categorize them according to the domains in which they are most relevant; in particular, we highlight the use of PKGs in medicine, finance, and education and research. We also categorize the different ways of constructing a PKG based on the source of data required for such constructions. Furthermore, we discuss the limitations of PKGs and suggest directions for future work.This article is categorized under: Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction Fundamental Concepts of Data and Knowledge > Knowledge Representation Technologies > Artificial Intelligence

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Section: Application Domains Of Pkgmentioning

confidence: 99%

Section: Construction Of Pkgmentioning

confidence: 99%

Section: Applications Of Pkgmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…(a) Personal knowledge graph based on lifelogs (Yen et al, 2021). (b) Personal research knowledge graph for researchers and academicians (Chakraborty et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations