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Constructing and Embedding Abstract Event Causality Networks from Text Snippets

Sendong Zhao, Quan Wang, Sean Massung, Bing Qin, Ting Liu, Bin Wang, ChengXiang Zhai
2017 Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17  
The abstract causality network is generalized from a specific one, with abstract event nodes represented by frequently cooccurring word pairs.  ...  Given the causality network and the learned embeddings, our model can be applied to a wide range of applications such as event prediction, event clustering and stock market movement prediction.  ...  and 61402465.  ... 
doi:10.1145/3018661.3018707 dblp:conf/wsdm/ZhaoWMQLWZ17 fatcat:4t255l3p5ndglefvp7zmunzrsy

Preliminary Investigation on Causality Information Retrieval

Pankaj Dadure, Partha Pakray, Sivaji Bandyopadhyay
2020 Forum for Information Retrieval Evaluation  
The main focus of this work is the extraction of causal relations from unstructured text data.  ...  In which, the data of the articles are split into a new instance for each separate text body of news articles and create embeddings. For similarity measurement, cosine similarity is used.  ...  , India for providing the infrastructural facilities and support.  ... 
dblp:conf/fire/DadurePB20 fatcat:oikimlyxrvaqhk55xtsbhcoyrq

Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality [article]

Arjun Choudhry, Mandar Sharma, Pramod Chundury, Thomas Kapler, Derek W.S. Gray, Naren Ramakrishnan, Niklas Elmqvist
2020 arXiv   pre-print
We then present results from a crowdsourced user study where participants were asked to recover causality information from two causality visualizations--causal graphs and Hasse diagrams--with and without  ...  Causality visualization can help people understand temporal chains of events, such as messages sent in a distributed system, cause and effect in a historical conflict, or the interplay between political  ...  The authors wish to thank all DARPA Causal Exploration collaborators for their support and encouragement.  ... 
arXiv:2009.02649v1 fatcat:5j725mocnffx7kc7cngpu73kuy

The Kappa platform for rule-based modeling

Pierre Boutillier, Mutaamba Maasha, Xing Li, Héctor F Medina-Abarca, Jean Krivine, Jérôme Feret, Ioana Cristescu, Angus G Forbes, Walter Fontana
2018 Bioinformatics  
network (DIN) and causal compression.  ...  Finally, we discuss how pathways might be discovered or recovered from a rule-based model by means of causal compression, as exemplified for early events in EGF signaling.  ...  Funding This work was sponsored by the Defense Advanced Research Projects Agency (DARPA) Big Mechanism Program and the US Army Research Office under grant numbers W911NF-14-1-0367 and W911NF-14-1-0395.  ... 
doi:10.1093/bioinformatics/bty272 pmid:29950016 pmcid:PMC6022607 fatcat:bacbdoatqnbjxnu6gc4s6inlxm

ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents

Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon (+3 others)
2021 Frontiers in Research Metrics and Analytics  
text mining techniques for chemical patents.  ...  their roles in chemical reactions, as well as reaction conditions; and (2) event extraction, which aims at identification of event steps relating the entities involved in chemical reactions.  ...  DN, ZZ, BF, and HY: data preparation, paper revision, and baseline design. SA, CD, CT, RH, and ZA: data preparation, paper revision, and organization of ChEMU lab.  ... 
doi:10.3389/frma.2021.654438 pmid:33870071 pmcid:PMC8028406 fatcat:w4vhhufqyfhshafwp4cjcobzdu

A Domain Specific Modeling Language Semantic Model for Artefact Orientation

Bunakiye R. Japheth, Ogude U. Cyril
2019 Zenodo  
These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.  ...  software layer with concrete syntax capable of determining design intents from domain expert.  ...  The events become more vivid in the form of text inputs from the UI, also, the template transformation has made it possible for the functionality of a new text editing platform i.e. the creation of the  ... 
doi:10.5281/zenodo.2576928 fatcat:kwrb3ybldfb2tl7vufw5m3a474

A Survey of Machine Narrative Reading Comprehension Assessments [article]

Yisi Sang, Xiangyang Mou, Jing Li, Jeffrey Stanton, Mo Yu
2022 arXiv   pre-print
differences among assessment tasks; and discuss the implications of our typology for new task design and the challenges of narrative reading comprehension.  ...  Based on narrative theories, reading comprehension theories, as well as existing machine narrative reading comprehension tasks and datasets, we propose a typology that captures the main similarities and  ...  Cloze Test takes a snippet of the original text with some pieces (usually entities) masked as blanks, with the goal of filling these blanks from a list of candidates.  ... 
arXiv:2205.00299v1 fatcat:ueifos3ymrhhfpd7hkbzdagxwy

Causality Mining in Natural Languages Using Machine and Deep Learning Techniques: A Survey

Wajid Ali, Wanli Zuo, Rahman Ali, Xianglin Zuo, Gohar Rahman
2021 Applied Sciences  
Among them, causality mining (CM) from textual data has become a significant area of concern and has more attention from researchers.  ...  , future scenario generation, medical text mining, behavior prediction, and textual prediction entailment.  ...  For event context word extension, they used BK, extracted from news articles in the form of a causal network to identify event causality.  ... 
doi:10.3390/app112110064 fatcat:btv66da5x5a73auogv5d3lp2bi

Event extraction for systems biology by text mining the literature

Sophia Ananiadou, Sampo Pyysalo, Jun'ichi Tsujii, Douglas B. Kell
2010 Trends in Biotechnology  
To computationally mine the literature for such events, text mining methods that can detect, extract and annotate them are required.  ...  Such interactions and their downstream effects are known as events.  ...  We would like to thank Paul Thompson and John McNaught (National Centre for Text Mining, University of Manchester) for their helpful comments and support in producing this manuscript.  ... 
doi:10.1016/j.tibtech.2010.04.005 pmid:20570001 fatcat:thw62syppnhd3jzd52ajqs5wum

Broad-coverage biomedical relation extraction with SemRep

Halil Kilicoglu, Graciela Rosemblat, Marcelo Fiszman, Dongwook Shin
2020 BMC Bioinformatics  
SemRep is a broad-coverage, interpretable, strong baseline system for extracting semantic relations from biomedical text.  ...  In this paper, we present an in-depth description of SemRep, an NLP system that extracts semantic relations from PubMed abstracts using linguistic principles and UMLS domain knowledge.  ...  Rindflesch for his design and development of early SemRep iterations and his supervision until his retirement and François-Michel Lang for his contributions to various aspects of SemRep.  ... 
doi:10.1186/s12859-020-3517-7 pmid:32410573 fatcat:2rsnzh7q4nghjdeh2kpqsxozyy

The Continuing Reinvention of Content-Based Retrieval: Multimedia Is Not Dead

William I. Grosky, Terry L. Ruas
2017 IEEE Multimedia  
Multimedia researchers and their publications can be represented as a graph/Web/network. Using the tools of network science, this network can be formally studied.  ...  7 than text.  ... 
doi:10.1109/mmul.2017.7 fatcat:35erkhh5kndr5kxzp5gqozygbq

NEVESIM: event-driven neural simulation framework with a Python interface

Dejan Pecevski, David Kappel, Zeno Jonke
2014 Frontiers in Neuroinformatics  
To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation  ...  NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language.  ...  The NEVESIM simulator was developed by Dejan Pecevski with contributions from David Kappel.  ... 
doi:10.3389/fninf.2014.00070 pmid:25177291 pmcid:PMC4132371 fatcat:l27ob3vuqracfj4tdsfeomxqvi

Ontology For Multimedia Applications

Hiranmay Ghosh, Santanu Chaudhury, Anupama Mallik
2013 The IEEE intelligent informatics bulletin  
This tutorial aims to provide a critical overview of the technology, and focuses on application of ontologies for multimedia applications.  ...  It establishes the need for a fundamentally different approach for a representation and reasoning scheme with ontologies for semantic interpretation of multimedia contents.  ...  Since text is the symbolic representation of human experience and is closest to the abstract model of the world, linguistic constructs (mostly, nouns, verbs and phrases) are used to express the domain  ... 
dblp:journals/cib/GhoshCM13 fatcat:33igmxulcrbcznw35grgez7iiy

Extracting Temporal and Causal Relations between Events [article]

Paramita Mirza
2016 arXiv   pre-print
We then combine the two extraction components into an integrated relation extraction system, CATENA---CAusal and Temporal relation Extraction from NAtural language texts---, by utilizing the presumption  ...  about event precedence in causality, that causing events must happened BEFORE resulting events.  ...  This shows that the concept of causality is more abstract than the concept of temporal order of events in a text.  ... 
arXiv:1604.08120v1 fatcat:fmd7z6hwyjhgphbrnc3mgpifde

The Elements of Temporal Sentence Grounding in Videos: A Survey and Future Directions [article]

Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou
2022 arXiv   pre-print
We construct a taxonomy of TSGV techniques and elaborate methods in different categories with their strengths and weaknesses.  ...  Connecting computer vision and natural language, TSGV has drawn significant attention from researchers in both communities.  ...  Specifically, video is continuous and causal relations between video events are usually adjacent, while words in query are discrete and demonstrate syntactic structure.  ... 
arXiv:2201.08071v1 fatcat:2k2if6dsyveinec2dmmujcmhkq
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