Výsledky vyhledávání - "Paramita Mirza"

{AligNarr}: {A}ligning Narratives on Movies

Autor: Paramita Mirza, Gerhard Weikum, Mostafa Abouhamra

Publikováno v: The 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing
ACL/IJCNLP (2)

High-quality alignment between movie scripts and plot summaries is an asset for learning to summarize stories and to generate dialogues. The alignment task is challenging as scripts and summaries substantially differ in details and abstraction levels

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04479de51f9402929fb27b68d5882b93
https://aclanthology.org/2021.acl-short.54

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Cardinality Extraction from Text for Ontology Learning

Autor: Monika Jain, Raghava Mutharaju, Paramita Mirza

Publikováno v: COMAD/CODS

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9dc77283b3b2b5fe78fee005e0782a6c
https://doi.org/10.1145/3371158.3371223

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CHARM: Inferring Personal Attributes from Conversations

Autor: Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum

Publikováno v: EMNLP (1)
The 2020 Conference on Empirical Methods in Natural Language Processing

Personal knowledge about users’ professions, hobbies, favorite food, and travel preferences, among others, is a valuable asset for individualized AI, such as recommenders or chatbots. Conversations in social media, such as Reddit, are a rich source

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5ba0e7d21af5b27ec626c143082dac1
https://doi.org/10.18653/v1/2020.emnlp-main.434

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Listening between the Lines: Learning Personal Attributes from Conversations

Autor: Anna Tigunova, Andrew Yates, Gerhard Weikum, Paramita Mirza

Publikováno v: WWW

Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation. In this work we address the acquisition of such knowledge, for personalization in downstream Web applications,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0a9afdbc25d45cc87def334bc02f601
http://arxiv.org/abs/1904.10887

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Discovering the Functions of Language in Online Forums

Autor: Youmna Ismaeil, Oana Balalau, Paramita Mirza

Publikováno v: Proceedings of the 5th Workshop on Noisy User-generated Text
W-NUT@EMNLP

In this work, we revisit the functions of language proposed by linguist Roman Jakobson and we highlight their potential in analyzing online forum conversations. We investigate the relationship between functions and other properties of comments, such

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::489f0b300fee4adfbfb3293dcf610e08
https://hdl.handle.net/21.11116/0000-0008-0405-E

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Coverage of Information Extraction from Sentences and Paragraphs

Autor: Paramita Mirza, Nitisha Jain, Simon Razniewski, Gerhard Weikum

Publikováno v: EMNLP/IJCNLP (1)

Scalar implicatures are language features that imply the negation of stronger statements, e.g., “She was married twice” typically implicates that she was not married thrice. In this paper we discuss the importance of scalar implicatures in the co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5000985c5efc36c8e4171bd3a15fb3c5
https://doi.org/10.18653/v1/d19-1583

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{KnowledgeNet}: {A} Benchmark Dataset for Knowledge Base Population

Autor: Jordan Schmidek, Denilson Barbosa, Filipe Mesquita, Paramita Mirza, Matteo Cannaviccio

Publikováno v: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing
EMNLP/IJCNLP (1)

KnowledgeNet is a benchmark dataset for the task of automatically populating a knowledge base (Wikidata) with facts expressed in natural language text on the web. KnowledgeNet provides text exhaustively annotated with facts, thus enabling the holisti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d774add11f435bb492fbd149bc234e16
https://hdl.handle.net/21.11116/0000-0008-0410-1

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Completeness-aware Rule Learning from Knowledge Graphs

Autor: Daria Stepanova, Simon Razniewski, Gerhard Weikum, Paramita Mirza, Thomas Pellissier Tanon

Publikováno v: IJCAI
The Semantic Web--ISWC 2017
Lecture Notes in Computer Science
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}
Twenty-Seventh International Joint Conference on Artificial Intelligence, Jul 2018, Stockholm, Sweden. ⟨10.24963/ijcai.2018/749⟩
Lecture Notes in Computer Science ISBN: 9783319682877
ISWC (1)

International audience; Knowledge graphs (KGs) are huge collections of primarily encyclopedic facts that are widely used in entity recognition, structured search, question answering , and other tasks. Rule mining is commonly applied to discover patte

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b2b42c90ee27dfd0602197ccd094843
https://doi.org/10.24963/ijcai.2018/749

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EMOFIEL

Autor: Paramita Mirza, Harshita Jhavar

Publikováno v: WWW (Companion Volume)

We present EMOFIEL, a system that identifies characters and scenes in a story from a fictional narrative summary, generates appropriate scene descriptions, identifies the emotion flow between a given directed pair of story characters in each interact

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::964cb77fd553ebfadcf0269620f730b4
https://doi.org/10.1145/3184558.3186989

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KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents

Autor: Paramita Mirza, Fariz Darari, Rahmad Mahendra

Publikováno v: Proceedings of the 12th International Workshop on Semantic Evaluation
SemEval@NAACL-HLT
Scopus-Elsevier

We present KOI (Knowledge of Incidents), a system that given news articles as input, builds a knowledge graph (KOI-KG) of incidental events. KOI-KG can then be used to efficiently answer questions such “How many killing incidents happened in 2017 t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40435084f0fc16ebf08fc756ae0679a1
https://hdl.handle.net/21.11116/0000-0002-A818-6

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