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Structuring Wikipedia Articles with Section Recommendations

Tiziano Piccardi, Michele Catasta, Leila Zia, Robert West
2018 The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18  
Structuring a new or already existing Wikipedia article with sections is a hard task for humans, especially for newcomers or less experienced editors, as it requires significant knowledge about how a well-written  ...  Sections are the building blocks of Wikipedia articles. They enhance readability and can be used as a structured entry point for creating and expanding articles.  ...  Using topic modeling To begin with, we leverage topical modeling of Wikipedia articles. The assumption is that articles containing similar topics should have a similar section structure.  ... 
doi:10.1145/3209978.3209984 dblp:conf/sigir/PiccardiCZ018 fatcat:tfhnw4oam5hxnogfyichhxdncy

CIRGIRDISCO at TREC 2013 Contextual Suggestion Track: Using the Wikipedia Graph Structure for Item-to-Item Recommendation

Muhammad Atif Qureshi, Arjumand Younus, Colm O'Riordan, Gabriella Pasi
2013 Text Retrieval Conference  
This is followed by a Wikipedia-based item-to-item similarity computation framework which uses the Wikipedia category-article structure to compute similarity between example locations rated by users and  ...  This is then used in an item-based nearest neighbor recommendation framework to recommend the locations based on given user profile ratings.  ...  Computation of Item-to-Item Similarity using Wikipedia Category-Article Structure The steps defined in section 2 enable us to create a number of suggested locations for each context.  ... 
dblp:conf/trec/QureshiYOP13 fatcat:d7eybgjdind5bm4hg3tyfzuzgy

Recommender System Based on User-generated Content

Denis Turdakov
2007 Spring Young Researchers Colloquium on Databases and Information Systems  
This paper describes a novel approach of building recommender systems for the Web with the aid of usergenerated content.  ...  Recommender systems apply statistical and knowledge discovery techniques to the problem of making recommendations during live user interaction.  ...  In every article of Wikipedia links guide users to associated articles, often with additional information, and lists of categories for each article organize Wikipedia articles in a taxonomic structure.  ... 
dblp:conf/syrcodis/Turdakov07 fatcat:es23mn5pvzgrlna4l7hgnsmiba

IntelWiki: Recommending Resources to Help Users Contribute to Wikipedia [chapter]

Mohammad Noor Nawaz Chowdhury, Andrea Bunt
2014 Lecture Notes in Computer Science  
Our approach, embedded in the IntelWiki prototype, aims to make it easier for users to create or enhance the free-form text in Wikipedia articles by: i) recommending potential reference materials, ii)  ...  A laboratory evaluation with 16 novice Wikipedia editors revealed that, in comparison to the default Wikipedia design, IntelWiki's approach has positive impacts on editing quantity and quality, and perceived  ...  , and allows users to interact with the recommended references within the Wikipedia editor.  ... 
doi:10.1007/978-3-319-08786-3_35 fatcat:uvucce66urduviekfp66nkctui

Kshitij: A Search and Page Recommendation System for Wikipedia

Phanikumar Bhamidipati, Kamalakar Karlapalem
2008 International Conference on Management of Data  
Though the algorithms are tested on Wikipedia, external systems that do not have access to structured data can benefit from the recommendations.  ...  In this paper, we present a generic recommendation system that utilizes the stored as well as dynamically extracted semantics from Wikipedia.  ...  The rest of this paper is organized as follows: We first explain the Wikipedia structure and our main idea in section 2.1.  ... 
dblp:conf/comad/BhamidipatiK08 fatcat:ebbssbu6zrgdro4thynhs25tom

Fast Linking of Mathematical Wikidata Entities in Wikipedia Articles Using Annotation Recommendation [article]

Philipp Scharpf and Moritz Schubotz and Bela Gipp
2021 arXiv   pre-print
In this paper, we present our approach to structure and speed up this process by supporting annotators with a system that suggests formula names and meanings of mathematical identifiers.  ...  We test our approach annotating 25 articles on We evaluate the quality and time-savings of the annotation recommendations.  ...  In the case of semi-structured Wikipedia articles, Wikimedia launched an additional structured database, Wikidata, for a language-independent grounding of concept entities [24] .  ... 
arXiv:2104.05111v1 fatcat:5dos7psi3venncggysyvtf2txm

Fast Linking of Mathematical Wikidata Entities in Wikipedia Articles Using Annotation Recommendation

Philipp Scharpf, Moritz Schubotz, Bela Gipp
2021 Companion Proceedings of the Web Conference 2021  
We evaluate the quality and time-savings of AI-generated formula and identifier annotation recommendations on a test selection of Wikipedia articles from the physics domain.  ...  Our contributions were accepted in 88% of the edited Wikipedia articles and 67% of the Wikidata items.  ...  In the case of semi-structured Wikipedia articles, Wikimedia launched an additional structured database, Wikidata, for a language-independent grounding of concept entities [23] .  ... 
doi:10.1145/3442442.3452348 fatcat:tonq7wwqebg3jkrctweksmyjlq

Reengineering the Wikipedia for Reputation

Thomas Rune Korsgaard, Christian D. Jensen
2009 Electronical Notes in Theoretical Computer Science  
We propose a recommendation system, which allows Wikipedia users to calculate a personalised rating for any article based on feedback (recommendations) provided by other Wikipedia users.  ...  A simple prototype of the proposed recommendation system is presented in this paper along with a preliminary evaluation of the prototype.  ...  An overview of the Wikipedia and the structure of Wikipedia articles is presented in Section 3. An outline of the Wikipedia Recommender System is presented in Section 4.  ... 
doi:10.1016/j.entcs.2009.07.040 fatcat:hnn6yyx7azeolmz2kaflodtw6i

Mining Web Analytics Data for Information Wikis to Evaluate Informal Learning

Heba M. Ismail, Boumediene Balkhouche, Saad Harous
2020 International Journal of Engineering Pedagogy (iJEP)  
In our paper, we present an effective recommendation system that provides easier and faster access to relevant content on Wikipedia to support informal learning.  ...  In addition, we evaluate the impact of personalized content recommendations on informal learning from Wikipedia and show how web analytics data can be used to get an in-sight on informal learning in similar  ...  Wikipedia recommender systems A few recommendation models have been proposed to provide article recommendations in Wikipedia.  ... 
doi:10.3991/ijep.v10i1.11713 fatcat:xw2mof5mqrbrvcvpndvjwjm7si

Time Based Tag Recommendation Using Direct and Extended Users Sets

Tereza Iofciu, Gianluca Demartini
2009 European Conference on Principles of Data Mining and Knowledge Discovery  
We show how it is possible to map the hyperlink and category structure of Wikipedia to the social tagging setting.  ...  The main contribution is a time-based methodology for recommending tags exploiting the structure in the dataset without knowledge about the content of the resources.  ...  The rest of the paper is structured as follows. In Section 2 we describe the proposed algorithms also showing the correspondence to the Wikipedia setting.  ... 
dblp:conf/pkdd/IofciuD09 fatcat:fsfvuepslrhyrik6pgbhu7glky

Entity Recommendations Using Hierarchical Knowledge Bases

Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth
2015 Extended Semantic Web Conference  
Recent developments in recommendation algorithms have focused on integrating Linked Open Data to augment traditional algorithms with background knowledge.  ...  We propose a content-based recommendation approaches that adapts a spreading activation algorithm over the DBpedia category structure to identify entities of interest to the user.  ...  This semi-structured data is the wikilinks added to Wikipedia articles by users.  ... 
dblp:conf/esws/CheekulaKD0S15 fatcat:krvhhjvxwrcqbdi6lmcdgp42fy

Exploiting Twitter and Wikipedia for the annotation of event images

Philip James McParlane, Joemon Jose
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
The results of our experiments show and highlight the merits of exploiting social media data for annotating event images, where we are able to achieve recommendation accuracy comparable with a state-of-the-art  ...  In this paper, we develop an image annotation model which exploits textual content from related Twitter and Wikipedia data which aims to overcome the discussed problems.  ...  In order to address noise present in social media streams, we applied natural language processing techniques and combined recommendations made with those computed from structured Wikipedia data.  ... 
doi:10.1145/2600428.2609538 dblp:conf/sigir/McParlaneJ14 fatcat:hnvmpjqa4rdmledotag46iwofa

WikiRef: Wikilinks as a route to recommending appropriate references for scientific Wikipedia pages [article]

Abhik Jana, Pranjal Kanojiya, Pawan Goyal, Animesh Mukherjee
2018 arXiv   pre-print
Unfortunately, the references which support the content of each Wikipedia entity page, are far from complete. Why are the reference section ill-formed for most Wikipedia pages?  ...  For Computer Science we achieve a notably good performance with a precision@1 of 0.44 for reference recommendation as opposed to 0.38 obtained from the most competitive baseline.  ...  Some of the representative recommended references along with the target Wikipedia articles are shown in Table 6 .  ... 
arXiv:1806.04092v2 fatcat:yisf2lybbbfzvbu6n4evf2mfhy

Advertising Keywords Recommendation for Short-Text Web Pages Using Wikipedia

Weinan Zhang, Dingquan Wang, Gui-Rong Xue, Hongyuan Zha
2012 ACM Transactions on Intelligent Systems and Technology  
In this article, we propose a novel algorithm for advertising keywords recommendation for short-text Web pages by leveraging the contents of Wikipedia, a user-contributed online encyclopedia.  ...  Wikipedia contains numerous entities with related entities on a topic linked to each other.  ...  The rest of this article is organized as follows. In Section 2, we discuss several related works about search advertising, keywords recommendation, and application of Wikipedia.  ... 
doi:10.1145/2089094.2089112 fatcat:b5dskprcejc2nmswnehtlnr374

Explicit Semantic Analysis for Enriching Content-Based User Profiles

Fedelucio Narducci, Giovanni Semeraro, Pasquale Lops, Marco de Gemmis
2011 Italian Information Retrieval Workshop  
A content-based recommender system suggests items similar to those previously liked by a user, therefore the recommendation process consists of matching up the features stored in a user profile with those  ...  The idea of this work is to represent content objects, and consequentially user profiles, in terms of Wikipedia-based concepts.  ...  In this way, the classical Bag of Words (BOW) representation can be augmented with knowledge-based features. This paper is structured as follows.  ... 
dblp:conf/iir/NarducciSLG11 fatcat:dj5bdke3rnbd5cumxqkq5ur7im
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