B-CWB: Bilingual Comparative Web Browser Based on Content-Synchronization and Viewpoint Retrieval

Nadamoto, Akiyo; Ma, Qiang; Tanaka, Katsumi

doi:10.1007/s11280-005-1316-8

Cited by 14 publications

(9 citation statements)

References 8 publications

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“…This enables the user to read news articles while comparing them with articles. The Bilingual Comparative Web Browser (B-CWB) [4] extends CWB to compare news articles in different languages.…”

Section: Related Workmentioning

confidence: 99%

Named Entity Oriented Difference Analysis of News Articles and Its Application

Kiritoshi

2016

IEICE Trans. Inf. & Syst.

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To support the efficient gathering of diverse information about a news event, we focus on descriptions of named entities (persons, organizations, locations) in news articles. We extend the stakeholder mining proposed by Ogawa et al. and extract descriptions of named entities in articles. We propose three measures (difference in opinion, difference in details, and difference in factor coverage) to rank news articles on the basis of analyzing differences in descriptions of named entities. On the basis of these three measurements, we develop a news app on mobile devices to help users to acquire diverse reports for improving their understanding of the news. For the current article a user is reading, the proposed news app will rank and provide its related articles from different perspectives by the three ranking measurements. One of the notable features of our system is to consider the access history to provide the related news articles. In other words, we propose a context-aware re-ranking method for enhancing the diversity of news reports presented to users. We evaluate our three measurements and the re-ranking method with a crowdsourcing experiment and a user study, respectively.

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Section: Related Workmentioning

confidence: 99%

Named Entity Oriented Difference Analysis of News Articles and Its Application

Kiritoshi

2016

IEICE Trans. Inf. & Syst.

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“…[4], [12], [13]. Nakatani et al [14] proposed a method to rank the results obtained using a search engine according to the degree of difficulty with the easiest to understand being first.…”

Section: Related Workmentioning

confidence: 99%

How can the Web help Wikipedia? A Study of Information Complementation of Wikipedia by the Web

Eklou

Asano

Yoshikawa

2012

IPSJ Online Transactions

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Abstract:With the huge amount of data on the Web, looking for desired information can be a time-consuming task. Wikipedia is a helpful tool because it is the largest, most-popular general reference site on the Internet. Most search engines rank Wikipedia pages among the top listed results. However, because many articles on Wikipedia are manually updated by users, several articles lack information and must be upgraded. That necessary information for updates can sometimes be found on the Web. Uprooting this information from the Web involves a time-consuming process of reading, analyzing and summarizing the information for the user. To support the user search process and to help Wikipedia contributors in the updating process of articles, we propose a method of finding valuable complementary information related to the Web. Experiments showed that our method was quite effective in retrieving important complementary information from Web pages.

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“…Their method is similar to ours as increasing the coverage constitutes also one of our target, although their goal is fundamentally dierent from ours which is upgrading the coverage of Wikipedia articles. Also many studies have been done on getting similar web pages such as [4,11,10]. Nakatani et al [12] proposed a method in order to rank the results obtained by a search engine according to the degree of diculty with the easiest to understand being rst.…”

Section: Related Workmentioning

confidence: 99%

How the web can help Wikipedia

Eklou

Asano

Yoshikawa

2012

Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication

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With the huge amount of data on the Web, looking for desired information can be a time consuming task. Wikipedia is a very helpful tool as it is the largest most popular general reference site on the internet. Most search engines rank Wikipedia pages among the top listed results. However, because many articles on Wikipedia are manually updated by users, there are several articles that lack information and need to be upgraded. Those lacking information can sometimes be found on the web. Uprooting this information from the web will involve a time consuming process of reading, analyzing and summarizing the information for the user . In order to support the user search process and help Wikipedia contributors in the updating process of articles, we propose a method of nding valuable complementary information on the web. Experiments showed that our method was quite eective in retrieving important complementary information from the web pages.

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B-CWB: Bilingual Comparative Web Browser Based on Content-Synchronization and Viewpoint Retrieval

Cited by 14 publications

References 8 publications

Named Entity Oriented Difference Analysis of News Articles and Its Application

Named Entity Oriented Difference Analysis of News Articles and Its Application

How can the Web help Wikipedia? A Study of Information Complementation of Wikipedia by the Web

How the web can help Wikipedia

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