A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories

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A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories
Authors
Takumi Yoshida
Ushio Inoue
Publication date
2013
DOI
10.1109/SNPD.2013.3
Links
Original

A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories - scientific work related to Wikipedia quality published in 2013, written by Takumi Yoshida and Ushio Inoue.

Overview

Social bookmarking services facilitate the addition of web page bookmarks by users, tagged with their choice of keywords. These services can employ personalized recommender systems to suggest newly added and potentially beneficial bookmarks from other users. The authors of this study have developed a novel strategy aimed at identifying users with similar interests and selecting appropriate bookmarks within a social bookmarking service. The method is deemed lightweight due to its utilization of a minimal, yet crucial set of tags from each user to discover worthwhile bookmarks for recommendations. The authors further enhance the potency of their method by incorporating the Wikipedia category database, which provides a robust solution to handle the wide-ranging tag diversity among users. The method was put to the test using the Hatena bookmarking service in Japan, where it significantly increased the number of relevant bookmark recommendations, with no substantial rise in irrelevant ones.

Relation to Information Quality on Wikipedia

The authors' method can have significant implications for the information quality on Wikipedia. By harnessing the Wikipedia category database to address tag diversity, this method provides a more nuanced understanding of user tags. This not only helps in creating more accurate recommendations, but can also enhance the quality of information categorization on Wikipedia.

Moreover, as the social bookmarking tags interact with the existing categorization structure of Wikipedia, they may reveal inconsistencies, gaps, or redundancies within the categories. Consequently, this interaction could lead to an iterative enhancement of Wikipedia's own information quality.

In essence, the authors' method improves the recommendation systems in social bookmarking services while also potentially contributing to an elevation in the quality of information categorization on Wikipedia. Such bidirectional improvements can enrich the user experience both on social bookmarking platforms and Wikipedia.

Embed

Wikipedia Quality

Yoshida, Takumi; Inoue, Ushio. (2013). "[[A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories]]".DOI: 10.1109/SNPD.2013.3.

English Wikipedia

{{cite journal |last1=Yoshida |first1=Takumi |last2=Inoue |first2=Ushio |title=A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories |date=2013 |doi=10.1109/SNPD.2013.3 |url=https://wikipediaquality.com/wiki/A_Bookmark_Recommender_System_based_on_Social_Bookmarking_Services_and_Wikipedia_Categories}}

HTML

Yoshida, Takumi; Inoue, Ushio. (2013). &quot;<a href="https://wikipediaquality.com/wiki/A_Bookmark_Recommender_System_based_on_Social_Bookmarking_Services_and_Wikipedia_Categories">A Bookmark Recommender System based on Social Bookmarking Services and Wikipedia Categories</a>&quot;.DOI: 10.1109/SNPD.2013.3.