no code implementations • 30 Sep 2024 • Divya Patel, Pathik Patel, Ankush Chander, Sourish Dasgupta, Tanmoy Chakraborty
To address this, we propose the iCOPERNICUS framework, a novel In-COntext PERsonalization learNIng sCrUtiny of Summarization capability in LLMs that uses EGISES as a comparative measure.
no code implementations • 29 Jun 2024 • Sourish Dasgupta, Ankush Chander, Parth Borad, Isha Motiyani, Tanmoy Chakraborty
However, a recent study argued that accuracy measures are inadequate for evaluating the degree of personalization of these models and proposed EGISES, the first metric to evaluate personalized text summaries.
no code implementations • 1 Mar 2023 • Priyanshi Gupta, Yash Kumar Atri, Apurva Nagvenkar, Sourish Dasgupta, Tanmoy Chakraborty
Current datasets and methods used for inline citation classification only use citation-marked sentences constraining the model to turn a blind eye to domain knowledge and neighboring contextual sentences.
no code implementations • 11 Feb 2018 • Sourish Dasgupta, Ankur Padia, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann
Ontology learning (OL) is the process of automatically generating an ontological knowledge base from a plain text document.
no code implementations • 15 Nov 2016 • Gaurav Maheshwari, Priyansh Trivedi, Harshita Sahijwani, Kunal Jha, Sourish Dasgupta, Jens Lehmann
Document similarity is the problem of estimating the degree to which a given pair of documents has similar semantic content.
no code implementations • 19 Mar 2015 • Sourish Dasgupta, Gaurav Maheshwari, Priyansh Trivedi
In this paper, we propose an algebraic similarity measure {\sigma}BS (BS stands for BitSim) for assigning semantic similarity score to concept definitions in ALCH+ an expressive fragment of Description Logics (DL).
no code implementations • 25 Dec 2013 • Sourish Dasgupta, Ankur Padia, Kushal Shah, Prasenjit Majumder
Hence, we also claim that such sentences requires special studies in the context of OL before any truly formal OL can be proposed.
no code implementations • 25 Dec 2013 • Sourish Dasgupta, Rupali KaPatel, Ankur Padia, Kushal Shah
The problem of Natural Language Query Formalization (NLQF) is to translate a given user query in natural language (NL) into a formal language so that the semantic interpretation has equivalence with the NL interpretation.
no code implementations • 24 Mar 2013 • Sourish Dasgupta, Ankur Padia, Kushal Shah, Rupali KaPatel, Prasenjit Majumder
Researchers in this field have been motivated by the possibility of automatically building a knowledge base on top of text documents so as to support reasoning based knowledge extraction.