Is the Paper Within Scope? Are You Fishing in the Right Pond?

Ghosal, Tirthankar; Sonam, Ravi; Ekbal, Asif; Saha, Sriparna; Bhattacharyya, Pushpak

doi:10.1109/jcdl.2019.00040

Cited by 11 publications

(8 citation statements)

References 9 publications

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“…These works identify like content by clustering the topics of the short text using [4,34]. The works [11,29,35] and GraphConfRec proposed by [16] are a set of hybrid approaches that combine the benefits of minimalistic paper content with author publication history. Citation graphs allude to topical similarities between the articles in the network [6].…”

Section: Related Workmentioning

confidence: 99%

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DeSCoVeR: Debiased Semantic Context Prior for Venue Recommendation

Rajanala

Pal

Singh

et al. 2022

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

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We present a novel semantic context prior-based venue recommendation system that uses only the title and the abstract of a paper. Based on the intuition that the text in the title and abstract have both semantic and syntactic components, we demonstrate that joint training of a semantic feature extractor and syntactic feature extractor collaboratively leverages meaningful information that helps in recommending venues for paper publication. The proposed methodology that we call DeSCoVeR first elicits these semantic and syntactic features using a Neural Topic Model and text classifier, respectively. The model then executes a transfer learning optimization procedure to perform a contextual transfer between the feature distributions of the Neural Topic Model and the text classifier during the training phase. DeSCoVeR also mitigates the document-level label bias using a Causal back-door path criterion and a sentence-level keyword bias removal technique. Experiments on the DBLP dataset show that DeSCoVeR outperforms the stateof-the-art methods.

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Section: Related Workmentioning

confidence: 99%

“…The works [11,29,35] and GraphConfRec proposed by [16] are a set of hybrid approaches that combine the benefits of minimalistic paper content with author publication history. Topical similarities between the papers using citation graphs are used in [6,30].…”

Section: Introductionmentioning

confidence: 99%

DeSCoVeR: Debiased Semantic Context Prior for Venue Recommendation

Rajanala

Pal

Singh

et al. 2022

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

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“…We count the number of common venues mentioned in the bibliography of citing & cited paper and normalize it with the number of unique venues in citing paper. Higher venue overlap would signify that the papers are in the same domain (Ghosal, Sonam, et al, 2019).…”

Section: Number Of Common Venues In Bibliography Of Citing and Cited Paper (F35)mentioning

confidence: 99%

“…We count the number of common authors mentioned in the bibliography of citing & cited paper and normalize it with the number of unique authors in citing paper (Ghosal, Sonam, et al, 2019).…”

Section: Number Of Common Authors In Bibliography Of Citing and Cited Paper (F36)mentioning

confidence: 99%

“…The knowledge discovery that ensues forms the basis of understanding a research problem, finding the previously explored frontiers, identifying research gaps, which eventually leads to the development of new ideas. However, with the exponential growth of scientific literature (including published papers and pre-prints) (Ghosal, Sonam, Ekbal, Saha, & Bhattacharyya, 2019), it is almost impossible for a researcher to go through the entire body of the scholarly works even in a very narrow domain. Citations play an important role here in finding the relevant articles that further topical knowledge.…”

Section: Introductionmentioning

confidence: 99%

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Towards establishing a research lineage via identification of significant citations

Ghosal

Tiwary

Patton

et al. 2021

Quantitative Science Studies

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Finding the lineage of a research topic is crucial for understanding the prior state of the art and advancing scientific displacement. The deluge of scholarly articles makes it difficult to locate the most relevant previous work. It causes researchers to spend a considerable amount of time building up their literature list. Citations play a crucial role in discovering relevant literature. However, not all citations are created equal. The majority of the citations that a paper receives provide contextual and background information to the citing papers. In those cases, the cited paper is not central to the theme of citing papers. However, some papers build upon a given paper, further the research frontier. In those cases, the concerned cited paper plays a pivotal role in the citing paper. Hence, the nature of citation the former receives from the latter is significant. In this work, we discuss our investigations towards discovering significant citations of a given paper. We further show how we can leverage significant citations to build a research lineage via a significant citation graph. We demonstrate the efficacy of our idea with two real-life case studies. Our experiments yield promising results with respect to the current state-of-the-art in classifying significant citations, outperforming the earlier ones by a relative margin of 20 points in terms of precision. We hypothesize that such an automated system can facilitate relevant literature discovery and help identify knowledge flow for a particular category of papers.

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