Protocol for E-Commerce data harvesting

Many retailers operate their business through e-commerce. Some of them provide Application Program Interface (API) to their affiliate users in efforts to selling their products. As most affiliate users are members to several retailers this will lead into two problems. Firstly, an affiliate user should implement different codes suitable to the requirements of each data provider. Secondly, the response from each data provider is different. As a consequence, affiliate users need to understand data structure of each data provider. Proposed solution to these problems is by utilizing a new protocol called E-Commerce Data Harvesting (ECDH) for the purpose of e-commerce data harvesting. Using the same protocol, affiliate users can utilize the same Uniform Resource Identifier (URI) to each data provider. In addition, we suggest GoodRelations ontology to support the data interoperability. This can address more industrial segments by combining GoodRelations with other ontologies. Combining both, protocol and ontology, we can establish an e-commerce data harvesting to provide smooth data interoperability.

[1]  Michael Kende Global internet report 2014: Open and sustainable access for all , 2014 .

[2]  Sangun Park,et al.  Ontology Mapping Between Heterogeneous Product Taxonomies in an Electronic Commerce Environment , 2007, Int. J. Electron. Commer..

[3]  Sean Bechhofer,et al.  Hello cleveland! Linked data publication of live music archives , 2013, 2013 14th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS).

[4]  Dennis L. Duffy Affiliate marketing and its impact on e‐commerce , 2005 .

[5]  Martin Hepp,et al.  Using BMEcat Catalogs as a Lever for Product Master Data on the Semantic Web , 2013, ESWC.

[6]  Sisi Zlatanova,et al.  Exploring ontologies for semantic interoperability of data in emergency response , 2011 .

[7]  Wang Jun Open Archives Initiative Protocol for Metadata Harvesting , 2005 .

[8]  Tao Huang,et al.  Research of web information retrieval based on metadata and OAI , 2008, 2008 IEEE International Conference on Granular Computing.

[9]  Flavius Frasincar,et al.  An Automatic Approach for Mapping Product Taxonomies in E-Commerce Systems , 2012, CAiSE.

[10]  Richard Cyganiak,et al.  Open eBusiness Ontology Usage: Investigating Community Implementation of GoodRelations , 2011, LDOW.

[11]  Mark A. Musen,et al.  The PROMPT suite: interactive tools for ontology merging and mapping , 2003, Int. J. Hum. Comput. Stud..

[12]  Andrea Zanella,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[13]  Jenn Riley,et al.  Semantics and syntax of dublin core usage in open archives initiative data providers of cultural heritage materials , 2005, Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '05).

[14]  Dean Allemang,et al.  Semantic Web for the Working Ontologist - Effective Modeling in RDFS and OWL, Second Edition , 2011 .

[15]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[16]  Martin Hepp,et al.  GoodRelations: An Ontology for Describing Products and Services Offers on the Web , 2008, EKAW.