2 Search Results for "Lakhotia, Arun"

Document
Research
DOI: 10.4230/TGDK.3.3.4
Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web

Authors: Florian Ruosch, Cristina Sarasua, and Abraham Bernstein

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract
In Argument Mining, predicting argumentative relations between texts (or spans) remains one of the most challenging aspects, even more so in the cross-document setting. This paper makes three key contributions to advance research in this domain. We first extend an existing dataset, the Sci-Arg corpus, by annotating it with explicit inter-document argumentative relations, thereby allowing arguments to be distributed over several documents forming an Argument Web; these new annotations are published using Semantic Web technologies (RDF, OWL). Second, we explore and evaluate three automated approaches for predicting these inter-document argumentative relations, establishing critical baselines on the new dataset. We find that a simple classifier based on discourse indicators with access to context outperforms neural methods. Third, we conduct a comparative analysis of these approaches for both intra- and inter-document settings, identifying statistically significant differences in results that indicate the necessity of distinguishing between these two scenarios. Our findings highlight significant challenges in this complex domain and open crucial avenues for future research on the Argument Web of Science, particularly for those interested in leveraging Semantic Web technologies and knowledge graphs to understand scholarly discourse. With this, we provide the first stepping stones in the form of a benchmark dataset, three baseline methods, and an initial analysis for a systematic exploration of this field relevant to the Web of Data and Science.
Cite as

Florian Ruosch, Cristina Sarasua, and Abraham Bernstein. Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 4:1-4:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ruosch_et_al:TGDK.3.3.4,
  author =	{Ruosch, Florian and Sarasua, Cristina and Bernstein, Abraham},
  title =	{{Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:33},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.4},
  URN =		{urn:nbn:de:0030-drops-252159},
  doi =		{10.4230/TGDK.3.3.4},
  annote =	{Keywords: Argument Mining, Large Language Models, Knowledge Graphs, Link Prediction}
}
Document
DOI: 10.4230/DagSemProc.06301.14
The Software Similarity Problem in Malware Analysis

Authors: Andrew Walenstein and Arun Lakhotia

Published in: Dagstuhl Seminar Proceedings, Volume 6301, Duplication, Redundancy, and Similarity in Software (2007)

Abstract
In software engineering contexts software may be compared for similarity in order to detect duplicate code that indicates poor design, and to reconstruct evolution history. Malicious software, being nothing other than a particular type of software, can also be compared for similarity in order to detect commonalities and evolution history. This paper provides a brief introduction to the issue of measuring similarity between malicious programs, and how evolution is known to occur in the area. It then uses this review to try to draw lines that connect research in software engineering (e.g., on "clone detection") to problems in anti-malware research.
Cite as

Andrew Walenstein and Arun Lakhotia. The Software Similarity Problem in Malware Analysis. In Duplication, Redundancy, and Similarity in Software. Dagstuhl Seminar Proceedings, Volume 6301, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{walenstein_et_al:DagSemProc.06301.14,
  author =	{Walenstein, Andrew and Lakhotia, Arun},
  title =	{{The Software Similarity Problem in Malware Analysis}},
  booktitle =	{Duplication, Redundancy, and Similarity in Software},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{6301},
  editor =	{Rainer Koschke and Ettore Merlo and Andrew Walenstein},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06301.14},
  URN =		{urn:nbn:de:0030-drops-9640},
  doi =		{10.4230/DagSemProc.06301.14},
  annote =	{Keywords: Software, software evolution, commonality, program similarity, code clones, code smells, malicious software, malware, worms, Trojans, viruses, spyware}
}
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