009 Eighth International Symposium on Natural Language Processing Improving research Paper Searching with Social Tagging A Preliminary Investigation P. Jomsri. S. Sanguansintukul and W. Choochaiwattana Abstract-The www provides an efficient way to store The tags can be useful for tasks such as search, navigatio and share information. Search engines and social or information extraction. Therefore. it is interesting to okmarking systems are important tools for web resource investigate how well a set of tags for the link to academic discovery. This study investigated three different indexing research papers on CiteULike contribute to search results approaches applied to CiteULike- a social bookmarking when they are used as research paper indexes system for tagging academie research papers. The indexing approaches here are known as: Tag only; Title with Abstract; In this paper, we investigated the use of social tagging to and Tag, Title with Abstract. These three indexing improve research paper indexing. We proposed an indexing approaches were evaluated using mean values of Normalized method using tagging information together with a title and Discount Cumulative Gain(NDCG). The preliminary results abstract of the paper(TTA). We refer to it as a"Tag Title illustrated that indexing using "Tag, Title, with with Abstract"indexing method. To evaluate the proposed performed the best. The initial evaluation indexing method, it was compared with two indexing implementation implied that these designs might im approaches: tagging information only indexing method and ccuracy and efficiency of web resouree searching mprove the title with abstract indexing method. We refer to them as bookmarking system, not only in academics but also in other domains "Tag Only' indexing method (T) andTitle with Abstraction"indexing method (TA)respectively The paper is structured as follows. First, we discuss L INTRODUCTION related work in Section i. we then describe framework There are an increasing number of people using the Sect son ai taghensectisnd re is re splen d discussion. documents on the internet. A social bookmarking system is wor Section V contains the Conclusion and Future is one important tool that allows people to search for also an important tool that allows people to share interesting web resources. It not only provides web IL. RELATED WORK resource sharing functions but also allows people to create Researchers who studied CiteULike include: Capocci a set of tags attached with the web resource (2007) analyzed the small-world properties of the Citeulike(wWw. cIteulike. org is a fusion of Web CiteULike folksonomy [2] and Santos-Neto(2007) based social bookmarking services and traditional explore presentin bibliographic management tools. It helps scientists characterizations of CiteULike and Bibsonomy that target researchers and academics store, organize, share and the management of scientific literature [15]. Toine Bogers discover links to academic research papers. It has been (2008)employed CiteULike to generate reading lists for publicly available to use since November 2004. Like many scientific articles based on the user's online reference successful tools, CiteULike has a flexible filing system library. They applied three different CF algorithms and ased on tags. These tags provide an open, quick and user- found that user-based filtering performs the best[14].Noel defined classification model that can produce interesting (2008)looked at the tagging behavior of people who were user-defined categorizations describing four frequently entered references[12]. The While the primary goal of these applications is to serve techniques from CiteULike have been applied to other the needs of individual users, the tags of each web academic searching, such as Farooq(2007)where four resource,links to academic research papers for each novel implications for designing the CiteSeer[4][5],[71 particular case, should also help other users to categorize, browse, and find items. The tags can also be used for Researchers who studied and improved social information discovery, sharing, and community ranking Suchanek(2008)found that tags are "meaningful Manuscript received June 15, 2009 >gging process is influenced by tag suggestions[12] while P. Jomsri, Department of Mathematics, Faculty of Scienc Chulalongkorn Univers communication in these systems in social tagging [13] PijitraJ@Student chula ac th Gelernter(2008)compares the information retrieval value S. Sanguansintukul, Department of Mathematics, Faculty of Science, of the cloud format tags and the tag words themselves as Chulalongk Thailand. (e-m found in the Library Thing catalog. Results also show that whether searchers are working toward research or personal Pundit University, Bangkok, Thailand (e-mail: worasit cha @dpu ac th) ends, high recall matters [6].A. Budura(2008 )present 978-1-4244-4139609525.00c2009IEEEAbstract— The WWW provides an efficient way to store and share information. Search engines and social bookmarking systems are important tools for web resource discovery. This study investigated three different indexing approaches applied to CiteULike – a social bookmarking system for tagging academic research papers. The indexing approaches here are known as: Tag only; Title with Abstract; and Tag, Title with Abstract. These three indexing approaches were evaluated using mean values of Normalized Discount Cumulative Gain (NDCG). The preliminary results illustrated that indexing using “Tag, Title, with Abstract” performed the best. The initial evaluation on our implementation implied that these designs might improve the accuracy and efficiency of web resource searching on social bookmarking system, not only in academics but also in other domains. I. INTRODUCTION here are an increasing number of people using the internet to exchange information. Thus, a search engine is one important tool that allows people to search for documents on the internet. A social bookmarking system is also an important tool that allows people to share interesting web resources. It not only provides web resource sharing functions but also allows people to create a set of tags attached with the web resource. CiteULike (www.CiteULike.org) is a fusion of Web￾based social bookmarking services and traditional bibliographic management tools. It helps scientists, researchers and academics store, organize, share and discover links to academic research papers. It has been publicly available to use since November 2004. Like many successful tools, CiteULike has a flexible filing system based on tags. These tags provide an open, quick and user￾defined classification model that can produce interesting user-defined categorizations. While the primary goal of these applications is to serve the needs of individual users, the tags of each web resource, links to academic research papers for each particular case, should also help other users to categorize, browse, and find items. The tags can also be used for information discovery, sharing, and community ranking. Manuscript received June 15, 2009. P. Jomsri, Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand. (e-mail: Pijitra.J@Student.chula.ac.th). S. Sanguansintukul, Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand. (e-mail: siripun.s@chula.ac.th). W. Choochaiwattana, Faculty of Information Technology,Dhurakij Pundit University, Bangkok,Thailand. (e-mail: worasit.cha@dpu.ac.th). The tags can be useful for tasks such as search, navigation or information extraction. Therefore, it is interesting to investigate how well a set of tags for the link to academic research papers on CiteULike contribute to search results when they are used as research paper indexes. In this paper, we investigated the use of social tagging to improve research paper indexing. We proposed an indexing method using tagging information together with a title and abstract of the paper (TTA). We refer to it as a “Tag Title with Abstract” indexing method. To evaluate the proposed indexing method, it was compared with two indexing approaches: tagging information only indexing method and title with abstract indexing method. We refer to them as “Tag Only” indexing method (T) and “Title with Abstraction” indexing method (TA) respectively. The paper is structured as follows. First, we discuss related work in Section II. We then describe Framework for social tagging based research paper searching in Section III. The Section IV is Result and Discussion. Finally, Section V contains the Conclusion and Future work. II. RELATED WORK Researchers who studied CiteULike include: Capocci (2007) analyzed the small-world properties of the CiteULike folksonomy [2] and Santos-Neto (2007) explored three main directions for presenting characterizations of CiteULike and Bibsonomy that target the management of scientific literature [15]. Toine Bogers (2008) employed CiteULike to generate reading lists for scientific articles based on the user’s online reference library. They applied three different CF algorithms and found that user-based filtering performs the best [14]. Noël (2008) looked at the tagging behavior of people who were describing four frequently entered references [12]. The techniques from CiteULike have been applied to other academic searching, such as Farooq (2007) where four novel implications for designing the CiteSeer [4], [5], [7] were presented. Researchers who studied and improved social tagging: Suchanek (2008) found that tags are “meaningful” and the tagging process is influenced by tag suggestions [12] while Thom-Santelli (2008) explored the use of tags for communication in these systems in social tagging [13]. Gelernter (2008) compares the information retrieval value of the cloud format tags and the tag words themselves as found in the LibraryThing catalog. Results also show that, whether searchers are working toward research or personal ends, high recall matters [6].A. Budura (2008) present Improving Research Paper Searching with Social Tagging – A Preliminary Investigation P. Jomsri, S. Sanguansintukul, and W. Choochaiwattana T 978-1-4244-4139-6/09/$25.00 ©2009 IEEE 152 2009 Eighth International Symposium on Natural Language Processing