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A Hybrid Tweet Contextualization System using IR and Summarization
2012
Conference and Labs of the Evaluation Forum
The INEX TC task has two main sub tasks, Focused IR and Automatic Summarization. In the Focused IR system, we first preprocess the Wikipedia documents and then index them using Nutch with NE field. ...
Stop words are removed and all NEs are tagged from each query tweet and all the remaining tweet words are stemmed using Porter stemmer. ...
We acknowledge the support of the IFCPAR funded Indo-French project "An Advanced Platform for Question Answering Systems" and the DIT, Government of India funded project "Development of Cross Lingual Information ...
dblp:conf/clef/BhaskarBB12
fatcat:d7sbdp2v6jedbil4iohgenpjmm
A Pipeline Tweet Contextualization System at INEX 2013
2013
Conference and Labs of the Evaluation Forum
This article describes a pipeline system and preliminary results for Tweet Contextualization at INEX 2013. The system consists of three steps: tweet analysis, passage retrieval and summarization. ...
Finally, a multi-document summarization system (MEAD) is used to generate the output document with a limit of 500 words. ...
contextualization system using IR and automatic summarization. ...
dblp:conf/clef/AnsaryTT13
fatcat:nwsmll5hbfde7cheeud3kkwbmi
Tweet Contextualization (Answering Tweet Question) - the Role of Multi-document Summarization
2013
Conference and Labs of the Evaluation Forum
In our system there are three major sub-systems; i) Offline multi-document summarization, ii) Focused IR and iii) online multi-document Summarization. ...
The Offline multi-document summarization system is based on document graph, clustering and sentence compression. In the Focused IR system, Wikipedia documents are indexed using Lucene with NE field. ...
of Cross Lingual Information Access (CLIA) System Phase II". ...
dblp:conf/clef/BhaskarBB13
fatcat:bdhrsixvhjft3jcitffjjad2f4
Answering Questions from Multiple Documents - the Role of Multi-Document Summarization
2013
Recent Advances in Natural Language Processing
The system clusters similar texts from the graph using this edge score. Each cluster gets a weight and has a cluster center. ...
Ongoing research work on Question Answering using multi-document summarization has been described. It has two main sub modules, document retrieval and Multi-document Summarization. ...
Acknowledgments We acknowledge the support of the DeitY, MCIT, Govt. of India funded project "Development of Cross Lingual Information Access (CLIA) System Phase II". ...
dblp:conf/ranlp/Bhaskar13
fatcat:mjw255widrfkxct2diozlxro2y
Towards Events Tweet Contextualization Using Social Influence Model and Users Conversations
2015
Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics - WIMS '15
To evaluate our approach, we construct a reference summary by asking assessors to manually select the most informative tweets as a summary. ...
In order, to make tweet understandable to a reader, it is therefore necessary to know their context. ...
The proposed approach in [6] described a hybrid tweet contextualization system using Information Retreival (IR) and Automatic Summarization (AS). ...
doi:10.1145/2797115.2797134
dblp:conf/wims/BelkarouiF15
fatcat:dwmuauybhzgw5f56wq4647kl4m
User-Tweet Interaction Model and Social Users Interactions for Tweet Contextualization
[chapter]
2015
Lecture Notes in Computer Science
To evaluate our approach, we construct a reference summary by asking assessors to manually select the most informative tweets as a summary. ...
In this paper, we propose an approach for tweet contextualization task which combines different types of signals from social users interactions to provide automatically information that explains the tweet ...
The approach proposed in [6] described a hybrid tweet contextualization system using Information Retreival (IR) and Automatic Summarization (AS). ...
doi:10.1007/978-3-319-24069-5_14
fatcat:g5ptv6pqcrgxtglvjuzxim6fbu
Conversational based method for tweet contextualization
2017
Vietnam Journal of Computer Science
We propose a specific method allowing to automatically contextualize tweets using information coming from social user interactions. ...
Bound to 140 characters, tweets are short and ambiguous by nature. It can be hard for a user without any kind of context to effectively understand what the tweet is about. ...
, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ...
doi:10.1007/s40595-016-0092-y
fatcat:akm2ekzkenezhnf4qee4pzujla
Testing a Statistical Word Stemmer based on Affixality Measurements in INEX 2012 Tweet Contextualization Track
2012
Conference and Labs of the Evaluation Forum
sed on 0xlity mesurementsF hese mesurements quntify three hrteristis of lngugeF sn this experiment we tested one strtE egy of stemming with three di'erent sizes of trining dtF he developed stemmer ws used ...
y the utomti summriztion system Cortex to preproess input texts nd produe redle summriesF ell summries were evluted s prt of the sxi PHIP weet gontextuliztion rkF e present the results of evlution nd ...
More details of the system of evaluation and the INEX 2012 Tweet Contextualization Track could be found in [1] . For this track we developed a stemmer based on morphological segmentation. ...
dblp:conf/clef/Mendez-CruzSU12
fatcat:xpfbjcoyvjfejajjocf6l2j2qm
Spatio-Temporal Small Worlds for Decentralized Information Retrieval in Social Networking
[article]
2012
arXiv
pre-print
Using a large Twitter dataset, we investigate these approaches and especially investigate the question in how far spatio-temporal contexts can act as a conceptual bracket implicating social and semantic ...
IR heuristics. ...
[48] for a hybrid document-/ index-distribution approach), and thus in most cases basically 'merely' distributes a conventional IR system over a P2P network, this architecture uses the actor's agent's ...
arXiv:1209.2868v1
fatcat:w3dbwdhb2vd3lgt74zneejmhnu
"When Numbers Matter!": Detecting Sarcasm in Numerical Portions of Text
2019
Proceedings of the Tenth Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
The actual system in place, however, are two deep learning (DL) models, CNN and attention network that obtains an F-score of 0.93 and 0.91 on our dataset of tweets containing numbers. ...
Initially, to get an insight into the problem, we implement a rulebased and a statistical machine learning-based (ML) classifier. ...
The authors would also like to thank Minali Upreti for helping with the diagrams and the anonymous reviewers for their valuable comments and feedback. ...
doi:10.18653/v1/w19-1309
dblp:conf/wassa/DubeyKSJB19
fatcat:zpugv3cd7ncmrd5xytcywl5psi
Implementation of Speedy Emergency Alert using Tweet Analysis
2016
Indian Journal of Science and Technology
Methods/Statistical analysis: This paper is to investigate the social problems on the basis of both economically and emotionally using twitter; summarizing the classified tweets into useful information ...
Further it uses stemming algorithm which is used for reducing variant forms of a word to a common form. Data are split and stored in the Data node and the index is maintained by the Name node. ...
Stemming Algorithm It is a process of linguistic normalization, in which variant forms of a word are reduced to a common form. It improves the performance of IR systems. ...
doi:10.17485/ijst/2016/v9i11/89390
fatcat:d7h3mbqibjhxngqk3odhakfdhy
Music Retrieval and Recommendation
2015
Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '15
We review approaches that extract features from all three data sources and combinations thereof and show how these features can be used for (large-scale) music indexing, music description, music similarity ...
Three factors play a central role in MIR research: (1) the music content, i.e., the audio signal itself, (2) the music context, i.e., metadata in the widest sense, and (3) the listeners and their contexts ...
as a digital audio file, a band's web page, a song's lyrics, or a tweet about a microblogger's current listening activity. ...
doi:10.1145/2766462.2767880
dblp:conf/sigir/KneesS15
fatcat:e2ibuiroeve3le7daazfwl4v4e
Augmented Understanding and Automated Adaptation of Curation Rules
[article]
2020
arXiv
pre-print
Data curation has been defined as activities and processes an analyst undertakes to transform the raw data into contextualized data and knowledge. ...
To address these challenges, in this dissertation, we present techniques, algorithms and systems for augmenting analysts in curation tasks. ...
., a Tweet in Twitter) into contextualized data and knowledge include extracting, enriching, linking, annotating and summarizing social data. ...
arXiv:2007.08710v1
fatcat:cw4ka6pzw5ev3hlfidpfllv5sy
A Multilingual System for Cyberbullying Detection: Arabic Content Detection using Machine Learning
2017
Advances in Science, Technology and Engineering Systems
This journal extends on a previous paper to elaborate on a solution for detecting and stopping cyberbullying. ...
A lot of research work proposed solutions for detecting cyberbullying in English language and a few more languages, but none till now covered cyberbullying in Arabic language. ...
Arabic tweets in Saudi Arabia were analyzed by Alhumoud, Albuhairi and Altuwaijri [73] . They analyzed the tweets using a hybrid approach. ...
doi:10.25046/aj020634
fatcat:7f332jkprnbybct3hjt5aktzba
Textual Similarity Measurement Approaches: A Survey (1)
2020
The Egyptian Journal of Language Engineering
Finding the similarity between terms is the essential portion of textual similarity, then used as a major phase for sentence-level, paragraph-level, and script-level similarities. ...
, and the nowadays trending Conversational Agents (CA), which is a program deals with humans through natural language conversation. ...
Finally, a Convolutional neural network (CNN) is used to capture more contextual information and semantic similarity computation. A. Omar and W. ...
doi:10.21608/ejle.2020.42018.1012
fatcat:a2fhtkub7nazlkgzqewqbb7koi
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