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Article
Publication date: 6 November 2017

Akiyo Nadamoto and Keigo Sakai

Recently, people usually use the internet to obtain travel information, when they plan their travel. They especially want to obtain sightseeing spot information from reviews, but…

Abstract

Purpose

Recently, people usually use the internet to obtain travel information, when they plan their travel. They especially want to obtain sightseeing spot information from reviews, but there are huge amounts of reviews of sightseeing spots. Users therefore cannot obtain important information from the reviews easily. As described herein, this paper aims to propose a system that automatically extracts and presents welcome news for sightseeing spots from reviews. This proposed Welcome-news is a “useful information” and “unexpected information” related to travel.

Design/methodology/approach

The flow for extracting Welcome-news from reviews is simple: A user inputs a sightseeing spot about which to get information; the system obtains reviews of the sightseeing spot and divides each sentence into reviews; the system extracts sentences including Welcome-news keyword(s), and the sentences become useful information; the system extracts unexpected information from useful information based on clustering, and it becomes Welcome-news; and the system presents all Welcome-news to the user.

Findings

This paper reports three findings: extraction of useful information for sightseeing spots based on Welcome-news keywords extracted by our experiment and using support vector machine (SVM); extraction of unexpected information for sightseeing spots by clustering; and automatic presentation of Welcome-news.

Originality/value

Numerous studies have extracted information from reviews based on some keywords. This proposed extraction of Welcome-news for travel not only uses keywords but also clusters based on topics. Furthermore, the proposed keywords include general keywords and unique keywords. The former appears for all kinds of sightseeing spots. The latter appears only for sightseeing spot. The authors extracted general keywords manually, and unique keywords using SVM.

Details

International Journal of Web Information Systems, vol. 13 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 3 April 2018

Yu Suzuki, Hiromitsu Ohara and Akiyo Nadamoto

This paper aims to propose a method for summarizing the topics of tweets using the Wikipedia category structure as common knowledge for supplementing the understanding of the…

Abstract

Purpose

This paper aims to propose a method for summarizing the topics of tweets using the Wikipedia category structure as common knowledge for supplementing the understanding of the Twitter user’s interests. There are many topics in the tweets, and the topics can be treated as a tree structure. However, when the topic hierarchy is constructed using existing hierarchal clustering approach, the granularity of tweet groups differs for each user. For summarizing the topics, identification of the topics which are heterogeneous and which are not is necessary because it is easy to understand if several groups are categorized into parent groups. However, if the group units are different for each user, a number of users’ interests cannot be summarized. If some tweets are grouped into the presidential election, and the others are into Donald Trump, there cannot be a count of how many users are interested in Donald Trump.

Design/methodology/approach

One solution of this issue is to construct topic structures by mapping one common tree structure. In this paper, a method is proposed for constructing the topic structure using the Wikipedia category tree similar to a common tree structure. The tweets are categorized, mapped to titles of articles in the Wikipedia category tree and then visualized as the hierarchal structure to the users.

Findings

The effectiveness of the proposed hierarchal topic structure is confirmed. In theme “politics”, the proposed method works well. The main reason is that there are many technical terms about politics in the Wikipedia categories and articles. It was found that a number of the terms of politics do not have multiple meanings, multiple semantics. However, in theme “sports”, the proposed method does not perform well. The main reason for this case is that there are a number of names of people present as topic names.

Originality/value

One important feature of the proposed method is that it is easy to grasp not only about the topics which are heterogeneous or homogeneous with each other but also consider the missing time when extracting topics. Another feature is that the topic structures for multiple users are easy to compare with each other.

Details

International Journal of Pervasive Computing and Communications, vol. 14 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 15 August 2016

Ryo Mashimo, Tatsuya Kitamura, Tomohiro Umetani and Akiyo Nadamoto

This paper aims to propose a system that generates dialogue scenarios automatically in real time from Web news articles. Then, the authors used the Manzai metaphor, a form of…

Abstract

Purpose

This paper aims to propose a system that generates dialogue scenarios automatically in real time from Web news articles. Then, the authors used the Manzai metaphor, a form of Japanese traditional humorous comedy, in the system. The generated Manzai scenario consists of snappy patter and a humorous misunderstanding of dialogue based on the gap of our structure of funny points. The authors create communication robots to amuse people with the generated humorous robot dialogue scenarios.

Design/methodology/approach

The authors propose the following: how to generate funny dialogue-based scenario from Web news and Web intelligence, automatically? How to create direction of robots based on the pre-experiment? The authors conducted experiments from three viewpoints, namely, effectiveness of Manzai scenarios as content, effectiveness of Manzai-Robots as a medium and familiarity of Manzai-Robots.

Findings

In this paper, the authors find two points, namely, the new communication style called “human–robots implicit communication-and bridging the knowledge gap using Web intelligence, to communicate smoothly between humans and robots.

Originality/value

Numerous studies have examined communication robots that mutually communicate with people. However, for several reasons, communicating smoothly with people is difficult for robots. One reason is the problem of communication style. Another is knowledge gaps separating humans and robots. The authors propose a new communication style to solve the problems and designate the communication style based on dialogue between robots as “human-robot implicit communication”. The authors then create communication robots to communicate with people naturally, smoothly and with familiarity according to their dialogue.

Details

International Journal of Web Information Systems, vol. 12 no. 3
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 31 August 2010

Akiyo Nadamoto, Eiji Aramaki, Takeshi Abekawa and Yohei Murakami

Community‐type content that are social network services and blogs are maintained by communities of people. Occasionally, community members do not understand the nature of the…

Abstract

Purpose

Community‐type content that are social network services and blogs are maintained by communities of people. Occasionally, community members do not understand the nature of the content from multiple perspectives, and so the volume of information is often inadequate. The authors thus consider it necessary to present users with missing information. The purpose of this paper is to search for the content “hole” where users of community‐type content missed information.

Design/methodology/approach

The proposed content hole is defined as different information that is obtained by comparing community‐type content with other content, such as other community‐type content, other conventional web content, and real‐world content. The paper suggests multiple types of content holes and proposes a system that compares community‐type content with Wikipedia articles and identifies the content hole. The paper first identifies structured keywords from the community‐type content, and extracts target articles from Wikipedia using the keywords. It then extracts other related articles from Wikipedia using the link graph. Finally, it compares community‐type content with the articles in Wikipedia and extracts and presents content holes.

Findings

Information retrieval looks for similar data. In contrast, a content‐hole search looks for information that is different. This paper defines the type of content hole on the basis of viewpoints. The proposed viewpoints are coverage, detail, semantics, and reputation.

Originality/value

The paper proposes a system for extracting coverage content holes. The system compares community‐type content with Wikipedia and extracts content holes in the community‐type content.

Details

International Journal of Web Information Systems, vol. 6 no. 3
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 1 June 2015

Yuki Yamamoto, Tadahiko Kumamoto and Akiyo Nadamoto

– The purpose of this paper is to propose a method of calculating the sentiment value of a tweet based on the emoticon role.

Abstract

Purpose

The purpose of this paper is to propose a method of calculating the sentiment value of a tweet based on the emoticon role.

Design/methodology/approach

Classification of emoticon roles as four types showing “emphasis”, “assuagement”, “conversion” and “addition”, with roles determined based on the respective relations to sentiment of sentences and emoticons.

Findings

Clustering of users of four types based on emoticon sentiment.

Originality/value

Formalization, using regression analysis, of the relation of sentiment between sentences and emoticons in all roles.

Details

International Journal of Pervasive Computing and Communications, vol. 11 no. 2
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 29 March 2013

Yuki Hattori and Akiyo Nadamoto

The information of social media is not often written in ordinary web pages. Nevertheless, it is difficult to extract such information from social media because such services…

1369

Abstract

Purpose

The information of social media is not often written in ordinary web pages. Nevertheless, it is difficult to extract such information from social media because such services include so much information. Furthermore, various topics are mixed in social media communities. The authors designate such important and unique information related to social media as tip information. In this paper, they aim to propose a method to extract tip information that has been classified by topic from social networking services as a first step in extracting tip information from social media.

Design/methodology/approach

Themes of many kinds exist in a social media community because users write contents freely. Then the authors first detect the topics from the community and cluster the comment based on the topics. Subsequently, they extract tip information from each cluster. In this time, the tip information is include a user's experience and it has common important words.

Findings

The authors used an experiment to confirm that their proposed method can extract appropriate tip information from a community that a user specifies. The average precision is 69 per cent. A comparison of the authors' proposed method and baseline which is without detection of topic and clustering, the average precision obtained using the authors' proposed method is 18 per cent greater than the baseline.

Originality/value

The authors have three points to extract tip information from social media: topic detection and clustering from the social media using LDA method; extracting an author's actual experiences; and creation of a tip keyword dictionary from user experiments.

Details

International Journal of Web Information Systems, vol. 9 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 11 November 2014

Mai Miyabe, Akiyo Nadamoto and Eiji Aramaki

– This aim of this paper is to elucidate rumor propagation on microblogs and to assess a system for collecting rumor information to prevent rumor-spreading.

Abstract

Purpose

This aim of this paper is to elucidate rumor propagation on microblogs and to assess a system for collecting rumor information to prevent rumor-spreading.

Design/methodology/approach

We present a case study of how rumors spread on Twitter during a recent disaster situation, the Great East Japan earthquake of March 11, 2011, based on comparison to a normal situation. We specifically examine rumor disaffirmation because automatic rumor extraction is difficult. Extracting rumor-disaffirmation is easier than extracting the rumors themselves. We classify tweets in disaster situations, analyze tweets in disaster situations based on users' impressions and compare the spread of rumor tweets in a disaster situation to that in a normal situation.

Findings

The analysis results showed the following characteristics of rumors in a disaster situation. The information transmission is 74.9 per cent, representing the greatest number of tweets in our data set. Rumor tweets give users strong behavioral facilitation, make them feel negative and foment disorder. Rumors of a normal situation spread through many hierarchies but the rumors of disaster situations are two or three hierarchies, which means that the rumor spreading style differs in disaster situations and in normal situations.

Originality/value

The originality of this paper is to target rumors on Twitter and to analyze rumor characteristics by multiple aspects using not only rumor-tweets but also disaffirmation-tweets as an investigation object.

Details

International Journal of Web Information Systems, vol. 10 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

Content available
Article
Publication date: 30 March 2012

209

Abstract

Details

International Journal of Web Information Systems, vol. 8 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

Content available
Article
Publication date: 31 August 2010

Ismail Khalil

396

Abstract

Details

International Journal of Web Information Systems, vol. 6 no. 3
Type: Research Article
ISSN: 1744-0084

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