Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Viktor Pekar"'
Publikováno v:
Government Information Quarterly. 39:101658
Opinion polls play an important role in modern democratic processes: they are known to not only affect the outcomes of elections, but also have a significant influence on government policy after elections. Recent years have seen large discrepancies b
Publikováno v:
Journal of the Association for Information Science and Technology. 71:43-54
This article addresses the problem of detecting crisis‐related messages on social media, in order to improve the situational awareness of emergency services. Previous work focused on developing machine‐learning classifiers restricted to specific
Autor:
Viktor Pekar
Publikováno v:
Proceedings of the Fourteenth International AAAI Conference on Web and Social Media
Aston Research Explorer
Aston Research Explorer
The paper addresses the problem of forecasting consumer expenditure from social media data. Previous research of the topic exploited the intuition that search engine traffic reflects purchase intentions and constructed predictive models of consumer b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd6be04fcdbe1bdf2335b5c4747f9751
https://publications.aston.ac.uk/id/eprint/41513/1/FULL_PekarV.1068.pdf
https://publications.aston.ac.uk/id/eprint/41513/1/FULL_PekarV.1068.pdf
Autor:
Viktor Pekar
Publikováno v:
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
instname
Consumer expenditure constitutes the largest component of Gross Domestic Product in developed countries, and forecasts of consumer spending are therefore an important tool that governments and central bank use in their policy-making. In this paper we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07a9354bbbaf6747802ddbc95940db47
https://publications.aston.ac.uk/id/eprint/38891/1/8337_23270_1_PB.pdf
https://publications.aston.ac.uk/id/eprint/38891/1/8337_23270_1_PB.pdf
Autor:
Viktor Pekar, Jane M. Binner
Publikováno v:
WASSA@EMNLP
Consumer spending is a vital macroeco- nomic indicator. In this paper we present a novel method for predicting future con- sumer spending from social media data. In contrast to previous work that largely re- lied on sentiment analysis, the proposed m
Publikováno v:
Lecture Notes in Business Information Processing ISBN: 9783319270326
SWQD
SWQD
Risk assessment is dependent on its application domain. Risk values consist of probability and impact factors, but there is no fixed, unique guideline for the determination of these two factors. For a precise risk-value calculation, an adequate colle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd7a4141763353ce9d8e37630c35f0b6
https://doi.org/10.1007/978-3-319-27033-3_13
https://doi.org/10.1007/978-3-319-27033-3_13
Autor:
Viktor Pekar, Shiyan Ou
Publikováno v:
Journal of Vacation Marketing. 14:145-155
Automated discovery and analysis of customer opinions on the web holds a lot of promise for present-day practices of market research and customer relationship management. Opinion mining attempts to come up with ways to automatically analyse subjectiv
Autor:
Viktor Pekar
Publikováno v:
Computer Speech & Language. 22:1-16
Event entailment is knowledge that may prove useful for a variety of applications dealing with inferencing over events described in natural language texts. In this paper, we propose a method for automatic discovery of pairs of verbs related by entail
Autor:
Viktor Pekar, Richard Evans
Publikováno v:
Literary and Linguistic Computing. 22:329-343
The present article is concerned with the problem of automatic database population via information extraction (IE) from web pages obtained from heterogeneous sources, such as those retrieved by a domain crawler. Specifically, we address the task of f
Publikováno v:
Machine Translation. 21:29-53
The identification of cognates has attracted the attention of researchers working in the area of Natural Language Processing, but the identification of false friends is still an under-researched area. This paper proposes novel methods for the automat