CSM: A Cloud Service Marketplace for Complex Service Acquisition

The cloud service marketplace (CSM) is an exploratory project aiming to provide “an AppStore for Services.” It is an intelligent online marketplace that facilitates service discovery and acquisition for enterprise customers. Traditional service discovery and acquisition are time-consuming. In the era of OneClick Checkout and pay-as-you-go service plans, users expect services to be purchased online efficiently and conveniently. However, as services are complex and different from software apps, the currently prevailing App Store based on keyword search is inadequate for services. In CSM, exploring and configuring services are an iterative process. Customers provide their requirements in natural language and interact with the system through questioning and answering. Learning from the input, the system can incrementally clarify users’ intention, narrow down the candidate services, and profile the configuration information for the candidates at the same time. CSM’s back end is built around the Services Knowledge Graph (SKG) and leverages data mining technologies to enable the semantic understanding of customers’ requirements. To quantitatively assess the value of CSM, empirical evaluation on real and synthetic datasets and case studies are given to demonstrate the efficacy and effectiveness of the proposed system.

[1]  Yihong Gong,et al.  Dynamic active probing of helpdesk databases , 2008, Proc. VLDB Endow..

[2]  Sergei Vassilvitskii,et al.  k-means++: the advantages of careful seeding , 2007, SODA '07.

[3]  Peter P. Chen The Entity-Relationship Model: Towards a unified view of Data , 1976 .

[4]  Tania Tudorache,et al.  A Generic Ontology for Collaborative Ontology-Development Workflows , 2008, EKAW.

[5]  Clement T. Yu,et al.  An effective approach to document retrieval via utilizing WordNet and recognizing phrases , 2004, SIGIR '04.

[6]  Jian Xu,et al.  Real time contextual collective anomaly detection over multiple data streams , 2014 .

[7]  Wei Peng,et al.  Mining the “Voice of the Customer” for Business Prioritization , 2012, TIST.

[8]  Xin Fu,et al.  Elicitation of term relevance feedback: an investigation of term source and context , 2006, SIGIR.

[9]  Peter P. Chen The entity-relationship model: toward a unified view of data , 1975, VLDB '75.

[10]  ChengXiang Zhai,et al.  Interactive sense feedback for difficult queries , 2011, CIKM '11.

[11]  Burr Settles,et al.  Active Learning Literature Survey , 2009 .

[12]  Richard M. Karp,et al.  Reducibility among combinatorial problems" in complexity of computer computations , 1972 .

[13]  Hai Yang,et al.  ACM Transactions on Intelligent Systems and Technology - Special Section on Urban Computing , 2014 .

[14]  Jos de Bruijn,et al.  Web Service Modeling Ontology , 2005, Appl. Ontology.

[15]  I. Stoica,et al.  A case for a coordinated internet video control plane , 2012, CCRV.

[16]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[17]  Tao Li,et al.  Intelligent cloud capacity management , 2012, 2012 IEEE Network Operations and Management Symposium.

[18]  Chen Tian,et al.  Optimizing cost and performance for content multihoming , 2012, SIGCOMM '12.

[19]  Christian Bizer,et al.  The Berlin SPARQL Benchmark , 2009, Int. J. Semantic Web Inf. Syst..

[20]  ChengXiang Zhai,et al.  Tapping into knowledge base for concept feedback: leveraging conceptnet to improve search results for difficult queries , 2012, WSDM '12.

[21]  Freddy Lécué,et al.  A Formal Model for Semantic Web Service Composition , 2005, SEMWEB.

[22]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[23]  Lei Zou,et al.  gStore: Answering SPARQL Queries via Subgraph Matching , 2011, Proc. VLDB Endow..

[24]  Wei Peng,et al.  An integrated framework on mining logs files for computing system management , 2005, KDD '05.

[25]  Richard M. Karp,et al.  Reducibility Among Combinatorial Problems , 1972, 50 Years of Integer Programming.

[26]  David A. Cohn,et al.  Active Learning with Statistical Models , 1996, NIPS.

[27]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[28]  ChengXiang Zhai,et al.  Term feedback for information retrieval with language models , 2007, SIGIR.

[29]  Xiaosong Ma,et al.  SigLM: Signature-driven load management for cloud computing infrastructures , 2009, 2009 17th International Workshop on Quality of Service.

[30]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[31]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[32]  Frank van Harmelen,et al.  WebPIE: A Web-scale Parallel Inference Engine using MapReduce , 2012, J. Web Semant..

[33]  Jennifer Widom,et al.  SimRank: a measure of structural-context similarity , 2002, KDD.

[34]  Tao Li,et al.  Natural event summarization , 2011, CIKM '11.

[35]  Makoto Iwayama,et al.  Relevance feedback with a small number of relevance judgements: incremental relevance feedback vs. document clustering , 2000, SIGIR '00.

[36]  Wei Peng,et al.  An Integrated Data-Driven Framework for Computing System Management , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[37]  Vipin Kumar,et al.  Introduction to Data Mining , 2022, Data Mining and Machine Learning Applications.

[38]  Tao Li,et al.  Event Mining: Algorithms and Applications , 2015 .

[39]  Tao Tao,et al.  The Future of Service Marketplaces in the Cloud , 2012, 2012 IEEE Eighth World Congress on Services.

[40]  Tao Li,et al.  ASAP: A Self-Adaptive Prediction System for Instant Cloud Resource Demand Provisioning , 2011, 2011 IEEE 11th International Conference on Data Mining.

[41]  Christos Faloutsos,et al.  Fast Random Walk with Restart and Its Applications , 2006, Sixth International Conference on Data Mining (ICDM'06).

[42]  Éva Tardos,et al.  Maximizing the Spread of Influence through a Social Network , 2015, Theory Comput..

[43]  Yang Zhou,et al.  Ranking Services by Service Network Structure and Service Attributes , 2013, 2013 IEEE 20th International Conference on Web Services.

[44]  Manish Marwah,et al.  Sustainable operation and management of data center chillers using temporal data mining , 2009, KDD.

[45]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[46]  Xiaowei Yang,et al.  CloudCmp: Shopping for a Cloud Made Easy , 2010, HotCloud.

[47]  Yizhou Sun,et al.  Mining heterogeneous information networks: a structural analysis approach , 2013, SKDD.

[48]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .