Výsledky vyhledávání - "Maike Erdmann"

Improving the extraction of bilingual terminology from Wikipedia

Autor: Kotaro Nakayama, Shojiro Nishio, Takahiro Hara, Maike Erdmann

Publikováno v: ACM Transactions on Multimedia Computing, Communications, and Applications. 5:1-17

Research on the automatic construction of bilingual dictionaries has achieved impressive results. Bilingual dictionaries are usually constructed from parallel corpora, but since these corpora are available only for selected text domains and language

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e9dab69760648307d40a9d32430eac30
https://doi.org/10.1145/1596990.1596995

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Extraction of Bilingual Terminology from a Multilingual Web-based Encyclopedia

Autor: Maike Erdmann, Takahiro Hara, Shojiro Nishio, Kotaro Nakayama

Publikováno v: Journal of Information Processing. 16:68-79

With the demand for bilingual dictionaries covering domain-specific terminology, research in the field of automatic dictionary extraction has become popular. However, the accuracy and coverage of dictionaries created based on bilingual text corpora a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::661fa599a406a61ab827c0a57081714f
https://doi.org/10.2197/ipsjjip.16.68

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Feature Based Sentiment Analysis of Tweets in Multiple Languages

Autor: Gen Hattori, Yasuhiro Takishima, Hiromi Ishizaki, Maike Erdmann, Kazushi Ikeda

Publikováno v: Web Information Systems Engineering – WISE 2014 ISBN: 9783319117454
WISE (2)

Feature based sentiment analysis is normally conducted using review Web sites, since it is difficult to extract accurate product features from tweets. However, Twitter users express sentiment towards a large variety of products in many different lang

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::559563c9d0a74b062cf55dabca518e3d
https://doi.org/10.1007/978-3-319-11746-1_8

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Automatic Labeling of Training Data for Collecting Tweets for Ambiguous TV Program Titles

Autor: Maike Erdmann, Erik Ward, Yasuhiro Takishima, Chihiro Ono, Gen Hattori, Kazushi Ikeda

Publikováno v: SocialCom

Twitter is a popular medium for sharing opinions on TV programs, and the analysis of TV related tweets is attracting a lot of interest. However, when collecting all tweets containing a given TV program title, we obtain a large number of unrelated twe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::efc29ba6013eddfae692157777bc1d7f
https://doi.org/10.1109/socialcom.2013.119

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Extraction and Annotation of Personal Cliques from Social Networks

Autor: Chihiro Ono, Maike Erdmann, Gen Hattori, Tomoya Takeyoshi

Publikováno v: SAINT

In microblogging services such as Twitter, users can choose whose posts they want to read by "following" other user accounts. Twitter users often have large social networks, thus many of them are overwhelmed with managing their network connections an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1dede6706f724523f826ec71fde8db3a
https://doi.org/10.1109/saint.2012.32

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Social Indexing of TV Programs: Detection and Labeling of Significant TV Scenes by Twitter Analysis

Autor: Maike Erdmann, Keiichiro Hoashi, Chihiro Ono, Masami Nakazawa

Publikováno v: AINA Workshops

Technology to analyze the content of TV programs, especially the extraction and annotation of important scenes and events within a program, is beneficial for users to enjoy recorded programs. In this paper, we propose a method of detecting significan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9d2d8495a5f78601bb4418503e22dd44
https://doi.org/10.1109/waina.2012.188

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Hierarchical Training of Multiple SVMs for Personalized Web Filtering

Autor: Tomoya Takeyoshi, Chihiro Ono, Gen Hattori, Matsumoto Kazunori, Maike Erdmann, DucDung Nguyen

Publikováno v: Lecture Notes in Computer Science ISBN: 9783642326943
PRICAI

The abundance of information published on the Internet makes filtering of hazardous Web pages a difficult yet important task. Supervised learning methods such as Support Vector Machines can be used to identify hazardous Web content. However, scalabil

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8fce2c5e2cc95b46dca7f218983a3e20
https://doi.org/10.1007/978-3-642-32695-0_5

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A Bilingual Dictionary Extracted from the Wikipedia Link Structure

Autor: Takahiro Hara, Kotaro Nakayama, Shojiro Nishio, Maike Erdmann

Publikováno v: Database Systems for Advanced Applications ISBN: 9783540785675
DASFAA

A lot of bilingual dictionaries have been released on the WWW. However, these dictionaries insufficiently cover new and domain-specific terminology. In our demonstration, we present a dictionary constructed by analyzing the link structure of Wikipedi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5b6a2faa67e23db6d69badf04f1e2191
https://doi.org/10.1007/978-3-540-78568-2_63

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