May 5, 2019

1159 words 6 mins read

Paper Group NANR 110

Paper Group NANR 110

Automatic Identification of Aspectual Classes across Verbal Readings. JUNLP at SemEval-2016 Task 13: A Language Independent Approach for Hypernym Identification. TALN at SemEval-2016 Task 14: Semantic Taxonomy Enrichment Via Sense-Based Embeddings. Deftor at SemEval-2016 Task 14: Taxonomy enrichment using definition vectors. SenticNet 4: A Semantic …

Automatic Identification of Aspectual Classes across Verbal Readings

Title Automatic Identification of Aspectual Classes across Verbal Readings
Authors Ingrid Falk, Fabienne Martin
Abstract
Tasks Machine Translation
Published 2016-08-01
URL https://www.aclweb.org/anthology/S16-2002/
PDF https://www.aclweb.org/anthology/S16-2002
PWC https://paperswithcode.com/paper/automatic-identification-of-aspectual-classes
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Framework

JUNLP at SemEval-2016 Task 13: A Language Independent Approach for Hypernym Identification

Title JUNLP at SemEval-2016 Task 13: A Language Independent Approach for Hypernym Identification
Authors Promita Maitra, Dipankar Das
Abstract
Tasks Natural Language Inference, Question Answering, Relation Extraction
Published 2016-06-01
URL https://www.aclweb.org/anthology/S16-1204/
PDF https://www.aclweb.org/anthology/S16-1204
PWC https://paperswithcode.com/paper/junlp-at-semeval-2016-task-13-a-language
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Framework

TALN at SemEval-2016 Task 14: Semantic Taxonomy Enrichment Via Sense-Based Embeddings

Title TALN at SemEval-2016 Task 14: Semantic Taxonomy Enrichment Via Sense-Based Embeddings
Authors Luis Espinosa-Anke, Francesco Ronzano, Horacio Saggion
Abstract
Tasks
Published 2016-06-01
URL https://www.aclweb.org/anthology/S16-1208/
PDF https://www.aclweb.org/anthology/S16-1208
PWC https://paperswithcode.com/paper/taln-at-semeval-2016-task-14-semantic
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Framework

Deftor at SemEval-2016 Task 14: Taxonomy enrichment using definition vectors

Title Deftor at SemEval-2016 Task 14: Taxonomy enrichment using definition vectors
Authors Hristo Tanev, Agata Rotondi
Abstract
Tasks
Published 2016-06-01
URL https://www.aclweb.org/anthology/S16-1210/
PDF https://www.aclweb.org/anthology/S16-1210
PWC https://paperswithcode.com/paper/deftor-at-semeval-2016-task-14-taxonomy
Repo
Framework

SenticNet 4: A Semantic Resource for Sentiment Analysis Based on Conceptual Primitives

Title SenticNet 4: A Semantic Resource for Sentiment Analysis Based on Conceptual Primitives
Authors Erik Cambria, Soujanya Poria, Rajiv Bajpai, Bjoern Schuller
Abstract An important difference between traditional AI systems and human intelligence is the human ability to harness commonsense knowledge gleaned from a lifetime of learning and experience to make informed decisions. This allows humans to adapt easily to novel situations where AI fails catastrophically due to a lack of situation-specific rules and generalization capabilities. Commonsense knowledge also provides background information that enables humans to successfully operate in social situations where such knowledge is typically assumed. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. Previous versions of SenticNet were focused on collecting this kind of knowledge for sentiment analysis but they were heavily limited by their inability to generalize. SenticNet 4 overcomes such limitations by leveraging on conceptual primitives automatically generated by means of hierarchical clustering and dimensionality reduction.
Tasks Dimensionality Reduction, Sentiment Analysis
Published 2016-12-01
URL https://www.aclweb.org/anthology/C16-1251/
PDF https://www.aclweb.org/anthology/C16-1251
PWC https://paperswithcode.com/paper/senticnet-4-a-semantic-resource-for-sentiment
Repo
Framework

So-Called Non-Subsective Adjectives

Title So-Called Non-Subsective Adjectives
Authors Ellie Pavlick, Chris Callison-Burch
Abstract
Tasks Natural Language Inference
Published 2016-08-01
URL https://www.aclweb.org/anthology/S16-2014/
PDF https://www.aclweb.org/anthology/S16-2014
PWC https://paperswithcode.com/paper/so-called-non-subsective-adjectives
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Framework

User Classification with Multiple Textual Perspectives

Title User Classification with Multiple Textual Perspectives
Authors Dong Zhang, Shoushan Li, Hongling Wang, Guodong Zhou
Abstract Textual information is of critical importance for automatic user classification in social media. However, most previous studies model textual features in a single perspective while the text in a user homepage typically possesses different styles of text, such as original message and comment from others. In this paper, we propose a novel approach, namely ensemble LSTM, to user classification by incorporating multiple textual perspectives. Specifically, our approach first learns a LSTM representation with a LSTM recurrent neural network and then presents a joint learning method to integrating all naturally-divided textual perspectives. Empirical studies on two basic user classification tasks, i.e., gender classification and age classification, demonstrate the effectiveness of the proposed approach to user classification with multiple textual perspectives.
Tasks Recommendation Systems
Published 2016-12-01
URL https://www.aclweb.org/anthology/C16-1199/
PDF https://www.aclweb.org/anthology/C16-1199
PWC https://paperswithcode.com/paper/user-classification-with-multiple-textual
Repo
Framework

Contrasting Vertical and Horizontal Transmission of Typological Features

Title Contrasting Vertical and Horizontal Transmission of Typological Features
Authors Kenji Yamauchi, Yugo Murawaki
Abstract Linguistic typology provides features that have a potential of uncovering deep phylogenetic relations among the world{'}s languages. One of the key challenges in using typological features for phylogenetic inference is that horizontal (spatial) transmission obscures vertical (phylogenetic) signals. In this paper, we characterize typological features with respect to the relative strength of vertical and horizontal transmission. To do this, we first construct (1) a spatial neighbor graph of languages and (2) a phylogenetic neighbor graph by collapsing known language families. We then develop an autologistic model that predicts a feature{'}s distribution from these two graphs. In the experiments, we managed to separate vertically and/or horizontally stable features from unstable ones, and the results are largely consistent with previous findings.
Tasks
Published 2016-12-01
URL https://www.aclweb.org/anthology/C16-1080/
PDF https://www.aclweb.org/anthology/C16-1080
PWC https://paperswithcode.com/paper/contrasting-vertical-and-horizontal
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Framework

Approximating Givenness in Content Assessment through Distributional Semantics

Title Approximating Givenness in Content Assessment through Distributional Semantics
Authors Ramon Ziai, Kordula De Kuthy, Detmar Meurers
Abstract
Tasks Reading Comprehension
Published 2016-08-01
URL https://www.aclweb.org/anthology/S16-2026/
PDF https://www.aclweb.org/anthology/S16-2026
PWC https://paperswithcode.com/paper/approximating-givenness-in-content-assessment
Repo
Framework

Nested Propositions in Open Information Extraction

Title Nested Propositions in Open Information Extraction
Authors Nikita Bhutani, H. V. Jagadish, Dragomir Radev
Abstract
Tasks Open Information Extraction, Question Answering, Reading Comprehension
Published 2016-11-01
URL https://www.aclweb.org/anthology/D16-1006/
PDF https://www.aclweb.org/anthology/D16-1006
PWC https://paperswithcode.com/paper/nested-propositions-in-open-information
Repo
Framework

The use of body part terms in Taiwan and China: Analyzing 血 xue blood' and 骨 gu bone’ in Chinese Gigaword v. 2.0

Title The use of body part terms in Taiwan and China: Analyzing 血 xue blood' and 骨 gu bone’ in Chinese Gigaword v. 2.0
Authors Ren-feng Duann, Chu-Ren Huang
Abstract
Tasks
Published 2016-10-01
URL https://www.aclweb.org/anthology/Y16-3024/
PDF https://www.aclweb.org/anthology/Y16-3024
PWC https://paperswithcode.com/paper/the-use-of-body-part-terms-in-taiwan-and
Repo
Framework

Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression

Title Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression
Authors Terra Blevins, Robert Kwiatkowski, Jamie MacBeth, Kathleen McKeown, Desmond Patton, Owen Rambow
Abstract Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used and a classifier for identifying tweets that express grieving and aggression.
Tasks
Published 2016-12-01
URL https://www.aclweb.org/anthology/C16-1207/
PDF https://www.aclweb.org/anthology/C16-1207
PWC https://paperswithcode.com/paper/automatically-processing-tweets-from-gang
Repo
Framework

Knowledge Base Population for Organization Mentions in Email

Title Knowledge Base Population for Organization Mentions in Email
Authors Ning Gao, Mark Dredze, Douglas Oard
Abstract
Tasks Entity Linking, Knowledge Base Population, Slot Filling
Published 2016-06-01
URL https://www.aclweb.org/anthology/W16-1305/
PDF https://www.aclweb.org/anthology/W16-1305
PWC https://paperswithcode.com/paper/knowledge-base-population-for-organization
Repo
Framework

Real-Time Speech Emotion and Sentiment Recognition for Interactive Dialogue Systems

Title Real-Time Speech Emotion and Sentiment Recognition for Interactive Dialogue Systems
Authors Dario Bertero, Farhad Bin Siddique, Chien-Sheng Wu, Yan Wan, Ricky Ho Yin Chan, Pascale Fung
Abstract
Tasks Dialogue Management, Emotion Recognition, Feature Engineering, Sentiment Analysis, Speech Recognition
Published 2016-11-01
URL https://www.aclweb.org/anthology/D16-1110/
PDF https://www.aclweb.org/anthology/D16-1110
PWC https://paperswithcode.com/paper/real-time-speech-emotion-and-sentiment
Repo
Framework

Summarising the points made in online political debates

Title Summarising the points made in online political debates
Authors Charlie Egan, Advaith Siddharthan, Adam Wyner
Abstract
Tasks Argument Mining
Published 2016-08-01
URL https://www.aclweb.org/anthology/W16-2816/
PDF https://www.aclweb.org/anthology/W16-2816
PWC https://paperswithcode.com/paper/summarising-the-points-made-in-online
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Framework
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