Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Federico Alberto Pozzi"'
The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision
Publikováno v:
World Wide Web. 20:831-854
The data-centric impetus and the development of online social networks has led to a significant amount of research that is nowadays more flexible in demonstrating several sociological hypotheses, such as the sentiment influence and transfer among use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84d09be744c90a7ed4a904add2fa0b7e
https://doi.org/10.1007/s11280-016-0419-8
https://doi.org/10.1007/s11280-016-0419-8
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 8:37-45
When an earthquake occurs, a huge amount of data is generated by social media users. Social networks play therefore a fundamental role in the development of decision support systems that could help both government and citizens. From user-generated co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9dd167f678377dccf51280b3b0a966b4
https://doi.org/10.1007/s12652-016-0373-4
https://doi.org/10.1007/s12652-016-0373-4
In this chapter we provide some background knowledge for the sentiment analysis research field, subsequently providing an overview of the current challenges related to the social network environment. The main content of the chapter is devoted to intr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6adfd97dfae43ac47fbcd69a2e7ccbd
https://doi.org/10.1016/b978-0-12-804412-4.00001-2
https://doi.org/10.1016/b978-0-12-804412-4.00001-2
In this chapter we provide some conclusions related to challenges previously detailed, discussing the potential future directions toward the next generation of sentiment analysis systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a01d592f66d4750c4afd8fbff24289d4
http://hdl.handle.net/10281/298708
http://hdl.handle.net/10281/298708
Publikováno v:
Decision Support Systems. 68:26-38
The huge amount of textual data on the Web has grown in the last few years rapidly creating unique contents of massive dimension. In a decision making context, one of the most relevant tasks is polarity classification of a text source, which is usual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee1372606ac3ebb2abd5e7f608377f6b
To capture the sentiment of messages, several expressive forms are investigated.Expressive signals enrich the feature space of baseline and ensemble classifiers.Only adjectives play a fundamental role as expressive signal.Pragmatic particles and expr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54ad9dd17d2d64bd6950aa6747fcdddc
http://hdl.handle.net/10281/131580
http://hdl.handle.net/10281/131580
Publikováno v:
DSAA
The automatic detection of sarcasm and irony in user generated contents is one of the most challenging task of Natural Language Processing. In this paper we address this problem by introducing Bayesian Model Averaging (BMA), an ensemble approach to t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c82c5a61fe8d4695989a35fced458b05
https://doi.org/10.1109/dsaa.2015.7344888
https://doi.org/10.1109/dsaa.2015.7344888
Publikováno v:
AI*IA 2013: Advances in Artificial Intelligence ISBN: 9783319035239
AI*IA
AI*IA
Sentiment Analysis for polarity classification on microblogs is generally based on the assumption that texts are independent and identically distributed (i.i.d). Although these methods are aimed at handling the complex characteristics of natural lang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13c26d6adede3af1696d68f8bf0a3fbb
http://hdl.handle.net/10281/59461
http://hdl.handle.net/10281/59461
Publikováno v:
Natural Language Processing and Information Systems ISBN: 9783642388231
NLDB
NLDB
One of the most relevant task in Sentiment Analysis is Polarity Classification. In this paper, we discuss how to explore the potential of ensembles of classifiers and propose a voting mechanism based on Bayesian Model Averaging (BMA). An important is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f19eda6a67cbc3605e7492d89bc0fd5
https://doi.org/10.1007/978-3-642-38824-8_16
https://doi.org/10.1007/978-3-642-38824-8_16