Abstract
Data service mashup provides a development fashion that integrates heterogeneous data from multiple data sources into a single Web application. This paper focuses on the problem of recommending useful suggestions for developing data service mashups based on the association relationship of data services. Firstly the data service association relationship is analyzed from three angles: the data dependence, inheritance and the potential association between data services. Based on the analysis, a measure of the data service association relationship called connectivity is proposed to assess the relationship of any two data services. Then a recommendation method is proposed to suggest the next useful data services based on the connectivity. The experimental evaluation demonstrates the utility of our method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hoang, D.D., Paik, H.-y., Benatallah, B.: An analysis of spreadsheet-based services mashup, ADC 2010. In: Proceedings of the Twenty-First Australasian Conference on Database Technologies, pp. 141–150, (2010)
Jhingran, A.: Enterprise information mashups: integrating information, simply. In: Proceedings of the 32nd International Conference on Very Large Databases, Seoul, Korea, pp 3–4, (2006)
Altinel, M., Brown, P., Cline, S., Kartha, R., Louie, E., Markl, V., Mau, L.,Ng, Y. H., Simmen, D.,Singh, A.: Damia: a data mashup fabric for intranet applications. In: Proceedings of the 33rd International Conference on Very Large Databases, Vienna, pp 1370–1373, (2007)
Guiling, W., Feng, Z., Yanbo, H.: An Approach to Situational Data Integration Based on Data Service Hyperlink [J]. Telecommun. Sci. 30(2), 51–59 (2014)
Yahoo Pipes, http://pipes.yahoo.com/pipes/
Liu, X., Huang, G., Mei, H.: Discovering homogeneous web service community in the user-centric web environment. IEEE Trans. Serv. Comput. 2(2), 167–181 (2009)
Wang, G., Yang, S., Han, Y.: Mashroom: end-user mashup programming using nested tables. WWW 2009: 861–870
Han, Y., Wang, G., Ji, G., Zhang, P.: Situational data integration with data services and nested table. SOCA 7(2), 129–150 (2013)
Heß, A., Johnston, E., Kushmerick, N.: ASSAM: A Tool for Semi-automatically Annotating Semantic Web Services. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 320–334. Springer, Heidelberg (2004)
Wang, G., Zhang, S., Liu, C., Han, Y.: A Dataflow-Pattern-Based Recommendation Approach for Data Service Mashups.In: IEEE International Conference on Services Computing, (2014, in press)
Han J, Kamber M.: Data Mining, Southeast Asia Edition: Concepts and Techniques[M]. Morgan kaufmann (2006)
Zijian, Z., Kohavi, R., Mason, L.: Real world performance of association rule algorithms. In: Proceedings of the seventh ACM SIGKDD International Conference on Knowledge discovery and data mining. ACM (2001)
Wang, G., Fang, J., Han, Y.: Interactive Recommendation of Composition Operators for Situational Data Integration. CSC, pp. 120–127 (2013)
Elmeleegy, H., Ivan, A., Akkiraju, R., Goodwin, R.: Mashup advisor: a recommendation tool for mashup development. In: ICWS 2008, IEEE Computer Society, pp. 337–344 (2008)
Greenshpan, O., Milo, T., Polyzotis, N.: Autocompletion for mashups. VLDB 2009,pp. 538–549 (2009)
Chen, H., Lu, B., Ni, Y., Xie, G., Zhou, C., Mi, J., Wu, Z.: Mashup by surng a web of data APIs. VLDB 2009, pp. 1602–1605 (2009)
Yang, J., Han, J., Wang, X., Sun, H.: MashStudio: An On-the-fly Environment for Rapid Mashup Development. In: Xiang, Y., Pathan, M., Tao, X., Wang, H. (eds.) IDCS 2012. LNCS, vol. 7646, pp. 160–173. Springer, Heidelberg (2012)
Roy Chowdhury, S., Daniel, F., Casati, F.: Efficient, Interactive Recommendation of Mashup Composition Knowledge. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds.) Service Oriented Computing. LNCS, vol. 7084, pp. 374–388. Springer, Heidelberg (2011)
Ma, Y., Lu, X., Liu, X.Z., Wang, X.D., Blake, M.B.: Data-driven synthesis of multiple recommendation patterns to create situational web mashups. Sci. China Inf. Sci. 56(8), 1–16 (2013)
Roy Chowdhury, S., et al.: Complementary assistance mechanisms for end user mashup composition. In: Proceedings of the 22nd International Conference on World Wide Web companion. International World Wide Web Conferences Steering Committee (2013)
Acknowledgment
This work is supported in part by Beijing Natural Science Foundation (No.4131001), Scientific Research Common Program of Beijing Municipal Commission of Education (KM201310009003), and The Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges Under Beijing Municipality (IDHT20130502).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Zhang, S., Wang, G., Zhang, Z., Han, Y. (2015). A Connectivity Based Recommendation Approach for Data Service Mashups. In: Benatallah, B., et al. Web Information Systems Engineering – WISE 2014 Workshops. WISE 2014. Lecture Notes in Computer Science(), vol 9051. Springer, Cham. https://doi.org/10.1007/978-3-319-20370-6_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-20370-6_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20369-0
Online ISBN: 978-3-319-20370-6
eBook Packages: Computer ScienceComputer Science (R0)