A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
TV program detection in tweets
2013
Proceedings of the 11th european conference on Interactive TV and video - EuroITV '13
Preserved Fulltext
In this paper, we present a solution to identify whether a tweet posted by a user refers to one among a set of known TV programs. ...
However, eliciting preferences from a tweet requires to understand if the tweet refers to a specific TV program, a task particularly challenging due to the nature of tweets -e.g., the limited length and ...
Tweets are mapped onto TV showsassuming that each tweet can be at most mapped onto a TV program -on the basis of the data available from the EPG (Electronic Programming Guide). ...
doi:10.1145/2465958.2465960
dblp:conf/euroitv/CremonesiPPT13
fatcat:y4xgda6oynenjahfre2txe4jey
Filtering microblogging messages for social tv
2011
Proceedings of the 20th international conference companion on World wide web - WWW '11
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
From this annotated data set, we train an initial classifier. The features are designed to capture the association between the TV program and the message. ...
We propose a bootstrapping approach to collecting microblogging messages related to a given TV program. ...
Current Social TV applications search for these messages by issuing queries to social networks with the full title of the TV program. ...
doi:10.1145/1963192.1963288
dblp:conf/www/DanFD11
fatcat:5m36b2owknh7rli4l25mp2uusm
RESLVE
2013
Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
In such settings, the lack of linguistic features and sparse lexical context result in a high degree of ambiguity and sharp performance drops of nearly 50% in the accuracy of conventional NED systems. ...
We address the Named Entity Disambiguation (NED) problem for short, user-generated texts on the social Web. ...
EXPERIMENTS
Data Collection and Preparation We collected tweets posted on Twitter, videos posted on YouTube, and photos posted on Flickr. ...
doi:10.1145/2487788.2487823
dblp:conf/www/MurnaneHL13
fatcat:3h4drygadrf5nd4xpknl64voau
RESLVE: Leveraging User Interest to Improve Entity Disambiguation on Short Text
[article]
2013
arXiv
pre-print
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
In such settings, the lack of linguistic features and sparse lexical context result in a high degree of ambiguity and sharp performance drops of nearly 50% in the accuracy of conventional NED systems. ...
We address the Named Entity Disambiguation (NED) problem for short, user-generated texts on the social Web. ...
EXPERIMENTS
Data Collection and Preparation We collected tweets posted on Twitter, videos posted on YouTube, and photos posted on Flickr. ...
arXiv:1304.2401v1
fatcat:ioagdwdqcbcchmqpdgkxfgcoxy
RESLVE
2013
Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
In such settings, the lack of linguistic features and sparse lexical context result in a high degree of ambiguity and sharp performance drops of nearly 50% in the accuracy of conventional NED systems. ...
We address the Named Entity Disambiguation (NED) problem for short, user-generated texts on the social Web. ...
EXPERIMENTS
Data Collection and Preparation We collected tweets posted on Twitter, videos posted on YouTube, and photos posted on Flickr. ...
doi:10.1145/2487788.2488162
dblp:conf/www/MurnaneHL13a
fatcat:ejghrqkqlrerba4pamp22xbjmm
Wikipedia based semantic smoothing for twitter sentiment classification
2013
2013 IEEE INISTA
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
We apply our approach to sentiment classification of tweets. ...
Sentiment classification is one of the important and popular application areas of text classification in which texts are labeled as positive and negative. ...
They showed how to automatically collect a corpus for sentiment analysis and opinion mining purposes. They performed linguistic analysis of the collected corpus. ...
doi:10.1109/inista.2013.6577649
fatcat:jvyyfalhojag5g7ybdql7mqtde
Multi-source named entity typing for social media
2016
Proceedings of the Sixth Named Entity Workshop
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Typed lexicons that encode knowledge about the semantic types of an entity name, e.g., that 'Paris' denotes a geolocation, product, or person, have proven useful for many text processing tasks. ...
Evaluation in the challenging domain of social media shows that multi-source learning improves performance compared with rule-based KB lookups, boosting typing results for some semantic categories. ...
We considered a corpus of 2,400 tweets collected by Ritter et al. (2011) . ...
doi:10.18653/v1/w16-2702
dblp:conf/aclnews/VexlerM16
fatcat:bbambkuanfbrrc7a3f3usnsiwi
D3.1 TV programme annotation model
2019
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
This deliverable describes also a number of tools that perform named entity recognition and disambiguation on both automatic transcription and true subtitles of TV programs. ...
TV programs) and which has been investigated during the first 6 months of the project. ...
Acknowledgements This work has been partially supported by the French National Research Agency (ANR) within the ASRAEL project (ANR-15-CE23-0018), the French Fonds Unique Interministériel (FUI) within the NexGen-TV ...
doi:10.5281/zenodo.4796668
fatcat:4yfr45rvojfzrha2lcgkmkpxtu
Proceedings of Symposium on Data Mining Applications 2014
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The symposium will provide opportunities for technical collaboration among data mining and machine learning researchers around the Saudi Arabia, GCC countries and Middle-East region. ...
SDMA is organized by MEGDAM to advance the state of the art in data mining research field and its various real world applications. ...
News Labeled by the Number of Tweets A collection of manually labeled documents was created. ...
arXiv:2001.11324v1
fatcat:ezplxohltvbvrggurw3hdkdhz4
Impact of Unreliable Content on Social Media Users during COVID-19 and Stance Detection System
2020
Electronics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Analysis of collected data was carried out in five phases where we investigate the engagement of E, D, Q, and N users, tone of the tweets, and the consequence upon repeated exposure of such information ...
A labeled dataset is prepared where each tweet is assigned one of the four reaction polarities, namely, E (endorse), D (deny), Q (question), and N (neutral). ...
Acknowledgments: This work was carried out during the tenure of an ERCIM Alain Bensoussan Fellowship Program. ...
doi:10.3390/electronics10010005
fatcat:hswgttd2pvhn7lm3zbvpeduizm
A linguistic approach for determining the topics of Spanish Twitter messages
2014
Journal of information science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
for multi-label classification tasks. ...
The TASS 2013 General corpus, a collection of tweets which has been specifically annotated to perform text analytics tasks, is used as the dataset in our evaluation framework. ...
Appendix A and Appendix B show the topic distribution of tweets in the collection, for both training and test sets. The classes of the training set are unbalanced. ...
doi:10.1177/0165551514561652
fatcat:f5x5lyjdtvhtlas2zapfpyq77a
Utilising Wikipedia for Text Mining Applications
2016
SIGIR Forum
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Supervised Learning Methods from Text Data Supervised learning methods are a category of methods that exploit training data (i.e., pairs of input data points with a label for the corresponding output point ...
Reputation Dimensions' Classification Task Using the feature sets described in 5.5.2, we train a random forest classifier over the training data and then use it to predict labels for the test data. ...
Appendix B
Use of Wikipedia Articles' Hyperlink for Filtering Task
B.1 Introduction Here, we explain our previous approach for addressing the filtering task in the context of CLEF RepLab 2013 filtering ...
doi:10.1145/2888422.2888449
fatcat:lck3kkxoazcj5powaqhjs6epty
What's Happening Around the World? A Survey and Framework on Event Detection Techniques on Twitter
2019
Journal of Grid Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We also describe and compare data collection techniques, the effectiveness and shortcomings of various Twitter and non-Twitterbased features, and discuss various evaluation measures and benchmarking methodologies ...
It explores recent research trends and techniques for event detection using Twitter data. ...
Supervised Learning Supervised learning is an approach that generates class labels from training data. The training data consists of a set of examples (typically vectors) and a class label. ...
doi:10.1007/s10723-019-09482-2
fatcat:lypwnpnmonb3laa3koftllchby
User-Generated Content (UGC) Credibility on Social Media Using Sentiment Classification
2019
النشرة المعلوماتیة فی الحاسبات والمعلومات
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
approach for measuring posts credibility. ...
This paper adapted some of the existing literature and concluded that many previous approaches have investigated information credibility on Twitter and a limited number of Facebook for proposing a new ...
Both classifiers were trained over labeled data, obtained using crowdsourcing tools. ...
doi:10.21608/fcihib.2019.107506
fatcat:w4vazjtyl5h6zdz2kol2vn5hsy
Lessons learnt from the Named Entity rEcognition and Linking (NEEL) challenge series
2017
Semantic Web Journal
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
tweets, ensuring high quality labelled data that facilitates comparisons between different approaches. ...
This problem has attracted the attention of industry and research communities, resulting in algorithms for the automatic extraction of semantics in tweets and linking them to machine readable resources ...
Acknowledgments This work was supported by the FREME project (GA no. 644771) and by the CLARIAH-CORE project financed by the Netherlands Organisation for Scientific Research (NWO). ...
doi:10.3233/sw-170276
fatcat:lr45tai2unbotp5nrag5z7pjxy
« Previous
Showing results 1 — 15 out of 740 results