Ontology Development for SMEs E-commerce website based on Content Analysis and its Recommendation System
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1 Ontology Development for SMEs E-commerce website based on Content Analysis and its Recommendation System Pagon Gatchalee, Zhoujun Li School of Computer Science and Engineering Beihang University Beijing, China Thepchai Supnithi Language and Semantic Technology Laboratory National Electronics and Computer Technology Center Bangkok, Thailand Abstract This paper describes ontology development for SMEs E-commerce website based on content analysis technique for getting knowledge and develops recommendation system based on this ontology. In this paper there are three main tasks that regard and lead the goal of this paper. Three main tasks are 1) content analysis for SMEs e-commerce website by using SMEs e-commerce in Thailand as sample group, this main task describes how to get knowledge about SMEs e-commerce website s module that will know which modules should be include in SMEs e-commerce website based on sample group in Thailand 2) Ontology development for SMEs e-commerce website as ontology domain by using knowledge from content analysis at 1) and develops ontology on HOZO ontology editor tool 3) Recommendation system for SMEs e-commerce website, this is the goal of this paper that uses knowledge from 1) and also knowledge from experts and uses ontology from 2) to develop recommendation system based on OAM framework. Keywords Content analysis; Ontology development; SMEs e- commerce website ontology; SMEs; E-commerce; recommendation I. INTRODUCTION Thailand is one of member country of ASEAN Economic Community that will be established in AEC in 2015 will affect Thailand and also other member countries on several areas especially economic development follow by AEC policies that one of important policies of AEC, it is the Small and medium-sized businesses (SMEs) development with using the e-commerce technology as the middleman between SMEs owner to another business or customer. Another important AEC policy is trying to stimulate all member countries to share and collaborate in many areas to improve their economies. Because of this, a lot of SMEs will collaborate across countries. However, the structure on developing SMEs in each countries are different and make it difficult to share knowledge among them. To overcome this problem, it is necessary to develop the SMEs e-commerce website ontology for SMEs e- commerce websites to be a backbone in communication which each other. We develop a recommendation system based on SMEs e- commerce website ontology to recommend sample SMEs e- commerce that match each SMEs owner requirement and this recommendation system can also show the ability of using ontology for SMEs e-commerce website development. II. CONTENT ANALYSIS FOR ONTOLOGY DEVELOPMENT A. Content analysis goal definition In the first step, we define the goal of this content analysis as follows Which modules should be included in E-commerce website for SMEs in Thailand that can develop ontology by knowledge from this content analysis. B. Assumption for result of content analysis Apart from content analysis s goal in previous subject (A.), we need to define assumption result of this content analysis for leading researchers to the content analysis way. From definition of SMEs [3], SMEs is the one type of corporation but the size is smaller than normal corporation, so we set an assumption for result of this content analysis as There are modules of corporate website that were bundled with modules of E-commerce website. C. Corporate website analysis From the assumption in B., for modules of corporate website, Paul and John [2] have analyzed corporate websites in Korea and presented website evaluation model that can conclude modules of corporate website as Company logo About company content that includes company structure, company profile and all contents about company. Membership (user system) 7
2 FAQs content that web page should have a Frequently Asked Questions section, so the users can find answers themselves if it is a common issue. Sitemap system that website should have a site map so the users can see an overview of the corporate web site and it better for SEO too. Product information and its promotions. Banners (advertising) Media (both videos and photos). Privacy and policy content that contain information regarding privacy and legal disclaimers. Search system for search all contents in website. Contact system Feedback Outside links (exchanged links) News and articles We use all above modules as initial guideline of SMEs e- commerce website s modules for the module in corporate s part. D. E-commerce analysis From definition of E-commerce [4] so we know e-commerce [7] website should have basic features as Shopping cart Online payment Product catalogue Ordering Security on website In the same way as C., we use above features as initial guideline of SMEs e-commerce website s modules for the module in e-commerce part. E. Content analysis for E-commerce website for SMEs From previous sections, we have the list of corporate website s modules and E-commerce s module that is possible to be modules of E-commerce website for SMEs thus we list these modules into content analysis document as initial modules for preparation before doing content analysis on SMEs e-commerce website. We need to list both modules from C., and D., as initial modules and do analysis again because when adapt both modules from corporate and e-commerce analysis then we have to make sure which modules should be included in SMEs e-commerce website that is the goal of this content analysis. In this content analysis, we use 100 SMEs e-commerce website in Thailand as sample group. For analysis process, can describe by using pseudo-code as WHILE getting modules of each website IF that module is not included in content analysis document Then IF is main module Then Insert new column in document by using module s name ELSE Then put module s name in the row of exist column (main module) END IF ELSE Then IF math with any exist column (main module) in document Then Put Y in the row of that column ELSE Then Put N or blank in the row of that column END IF END IF END WHILE Conclusion, we make 37 columns in content analysis document that can list as Website Intro page Header Footer Company information Contact detail (without form) Contact detail with form Jobs opening Content/News Comment system Guestbook News feed News letter Banner system Link exchange Multi language Content search system Fonts selector Social network (Youtube/Twitter/Facebook/etc.) widget or links Product catalogue Related product showing Featured product showing 8
3 Shopping cart with online payment system Payment detail (no shopping cart) FAQs page Customer support system Product search system User system Web board/forum Mobile/Tablet viewing support Statistics log Delivery SEO system Poll system Is CMS or not? Main language Brief description From above, we get 34 main modules that we mark them as column of document (except Website, Main language and Brief description) that can show as fig 1) Fig 1. Content analysis document for SMEs e-commerce website F. Content analysis result From D., in content analysis form, we get 2 main results as 1) Main SMEs e-commerce website module that denoted as column For this result, we can know which modules appear on each website that we do analysis and as already mentioned in E., there are 34 columns that denoted as main modules and we put Y in each row of this column, if that website contains that column module otherwise put N or just leave it blank. For this result, we will evaluate Y and N (or blank) that we will get how many websites have that module and can conclude which modules will be main modules and should be included in SMEs e-commerce website. 2) Sub module of main modules Apart from putting Y or N (or blank) for the row of each module column in content analysis document, we put sub module of each main module (column) that we can define as its hierarchy. G. Content analysis result evaluation with experts This step, we need experts to confirm content analysis result about website modules in SMEs e-commerce website that we use interview as method to get knowledge from experts. 1) Who are experts? In this paper, there are 2 groups of experts as SMEs experts (5 persons) and E-commerce website development experts (5 persons). For criteria of expert selections, SMEs or E-commerce website owner. Have experience at least 1 year. But if is not owner, uses below criteria Obtained Master degree or above. Have experiences in that expert field at least 5 years (if not get Master degree or above, need to have wellknown workings or working in well-known company in Thailand. 2) Experts decision 9
4 Experts confirm to use modules that from content analysis but need to rid some modules as a) Newsletter Reason for rid it out: Can use social network instead and if website has user system so can send to all users with their s in database directly so do not need newsletter anymore. b) Guestbook Reason for rid it out: It s old-fashioned technology. c) Poll system Reason for rid it out: It s old-fashioned technology. d) Intro Page Reason for rid it out: It s common structure of website so do not need mention to it as module. e) Header Reason for rid it out: It s common structure of website so do not need mention to it as module. f) Footer Reason for rid it out: It s common structure of website so do not need mention to it as module. Finally, we get experts comments about modules such as new knowledge; some restrictions and etc. follow by expert s knowledge and experiences that we use those comments to define property, hierarchy level in ontology development part as well as creating the rules in the recommendation system. III. A. Ontology domain PREPARE YOUR PAPER BEFORE STYLING We define the ontology domain is SMEs e-commerce website in Thailand that will focus on SMEs e-commerce website s modules that get knowledge from content analysis in II. B. Ontology development process SMEs e-commerce website ontology was developed by using the HOZO ontology editor [8] that we develop ontology for SMEs e-commerce website follow by ontology life cycle [1]. The SMEs e-commerce website ontology consists of 177 classes both high-level classes and its sub classes that from fig 2., all classes in this ontology are sub class of Any class. There are 2 high-level classes that are major concepts of this ontology. The first is SMEs web as fig 3. 1) SMEs web class From fig 3., there are 7 properties as a) SMEs_web_module It is property that is connected to SMEs module class and this property has relationship with SMEs web class as Part-of. b) web_name It is property that for website name. Relationship type is Attribute of. c) web_url It is property that for website url. Relationship type is Attribute of. d) main language It is property that is connected to language class to describe about main language to used in this SMEs web. Relationship type is Part-of. e) is_made_by_cms It is property that is connected to CMS class to describe what CMS that use in this SMEs web. Relationship type is Part-of. f) is_subdomain It is property that for regconize this website is just subdomain of another site or not. Relationship type is Attribute-of. g) web_id It is property that for website id. It will be used as unique key of this class. Relationship type is Attribute of. 2) SMEs module class Another one major concept of this ontology is SMEs module that from fig 4., there are 11 sub classes that denoted as groups of SMEs module as Content system SEO system Advertising Statistics service Search system Communication Shop Mobile viewing Language selector Corporate User For properties of SMEs module class, there are 2 properties as a) module_id It is property for module id that use as unique key of this class. Relationship type is Attribute-of. b) module_name It is property for module name of this class. Relationship type is Attribute-of. 10
5 Fig 2. All classes concepts in the SMEs e-commerce website ontology Fig 3. SMEs web class s related concepts in the SMEs e-commerce web ontology IV. RECOMMENDATION SYSTEM FOR SMES E-COMMERCE WEBSITE CONTRUCTION A. Recommendation system development and its goal After we done ontology development, we create a prototype of recommendation system based on OAM framework [4]. It was developed by Language and Semantic Technology Laboratory, National Electronics and Computer Technology Center. In previous researches, there are several researches that were developed on OAM such as food recommendation system [5] based on user s health status and nutrition goals and another interesting project as Activity Recognition in Smart Home Domain [6]. For the goal, this recommendation system will recommend sample websites that are matched with user requirement rules. Fig 4. SMEs module class s related concepts in the SMEs e-commerce web ontology B. Example rules From content analysis result and expert knowledge, we can develop recommendation system with this knowledge and for this section, can show example rules as 1) IF SMEs owner has employees who can manage website >1 person THEN SMEs website should have contact system 2) IF (SMEs owner want the shopping cart module) and (Have no knowledge how to develop system) THEN Using online shop creation system 3) IF (SMEs owner have a few knowledge to develop website) and (Have a bit time to develop) and (Want to save the time and cost) THEN Using CMS 11
6 C. Recommendation system for SMEs e-commerce website construction From example rules in B., can insert them into recommendation rule management on OAM framework [4] as fig 5. this recommendation rule that can click on link to see each SMEs web detail such as website s id(in database), website s URL and website s main language V. CONCLUSIONS In this research, we develop recommendation system for SMEs e-commerce website in Thailand based on OAM framework that will recommend sample website to users that match recommendation rule. Apart from recommendation system, we get SMEs e-commerce website ontology that uses content analysis to get knowledge and develop this ontology that can use SMEs e-commerce website ontology to develop another system based on this ontology and also can use content analysis of this research as guideline to get knowledge to develop other ontologies in the future. REFERENCES [1] N.F.Noy and D.L. McGuiness, Ontology development 101: a guide to creating your first ontology, Stanford Knowledge Systems Laboratory Technical Report KSL and Stanford Medical Informatics Technical Report SMI , Fig 5. All sample recommendation rules in recommendation system From fig 5., when we click on each recommendation rule link then we will get description as fig 6. [2] Sung P, Paynter, J., Content Analysis of Korean Corporate Web Sites, National Advisory Committee on Computing Qualifications 19th: Annual Conference, National Advisory Committee on Computing Qualifications, [3] Chooprayoon, Vasin.A study of factors influencing the adoption of e- commerce technology in small and medium enterprises (SMEs) in the kingdom of Thailand, Murdoch University, Faculty of Law, Business and Information Technology. [4] Buranarach, M., Thein, Y. M., and Supnithi, T., A Community-driven Approach to Development of an Ontology-based Application Management Framework, Proceedings of the 2nd Joint International Semantic Technology Conference (JIST2012), LNCS, Springer, December [5] Suksom, N., Buranarach, M., Thein, Y.M., Supnithi, T., and Netisopakul, P., A Knowledge-based Framework for Development of Personalized Food Recommender System, Proceedings of the 5th International Conference on Knowledge, Information and Creativity Support Systems (KICSS2010), November [6] Wongpatikaseree, K., Ikeda, M., Buranarach, M., Supnithi, T., Lim, A. O., and Tan Y., Location-based Concept in Activity Log Ontology for Activity Recognition in Smart Home Domain, Proceedings of the 2nd Joint International Semantic Technology Conference (JIST2012), LNCS, Springer, December 2012, Best In-Use Track Paper Award. Fig 6. Recommendation rule information with sample instances that match with recommendation rule From fig 6. at above, The recommendation rule is show sample website that not subdomain then it shows all recommendation data that is sample SMEs web that match with [7] Keretho, Somnuk, and Paisan Limsit E-Commerce the Way of Business in Thailand. An International Workshop on Electronic Commerce Policy and Regional Cooperation, Bangkok June 2002, APEC Electronic Commerce Training Center 2002 [cited 12 July 2006], accessed November ; ppt/pdf/ec_way_business_in_thailand.pdf. [8] Control Device Division, Enegate Co, ltd. Mizoguchi Laboratory, The Institute of Scientific and Industrial Research, Osaka University. 2011, Hozo Ontology Editor (Distributed Development Version) Operating Manual, accessed November ; 12
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