Classification is the basic method for humans to recognize and manage things. Different classification methods can be used to classify one set of things no matter what forms they are and whether they are centralized or decentralized. The Resource Space Model is to efficiently organize and manage the contents of resources by a space consists of multiple classification methods.

Theory, Model and Method

Different from distance space, an axis of the resource space represents a classification method. A coordinate, which can be a tree structure, represents a complex class. There could be no order between coordinates. For raising the efficiency and correctness of operations on resource space, a set of normal forms to normalize the resource space is defined. The 1st Normal Form is about no redundancy, the 2nd Normal Form is about independency of classifications, and the 3rd Normal Form is about the orthogonality between axes. Normal forms are then extended to 2+NF and 4NF to loose or tighten the constraints on space. The schema of resource space is proposed to regulate the instances of resource space. The topological characteristic and the relations between the normal forms and the operations such as merge and join are unveiled. The operation language for Resource Space Model is designed for querying and managing resources. A complete set of operations is given through investigating the completeness of operations. The integrity of resource space is proposed to ensure the appropriate operations.

To deal with the inexactness of classification and the uncertainty of storing and querying resources, the Resource Space Model is extended to the Probabilistic Resource Space Model so as to deal with the uncertainty. The effect of the Probabilistic RSM enables resources to be distributed evenly in the space.

The method of mappings between RSM, relational database and OWL (Web Ontology Language) is proposed to unveil the uniformity in the diversity of models. Different models have different characteristics, how to make use of the characteristics of different models is studied, so the method of integrating the three models is proposed. This provides an approach to integrating more semantic models. The method of deploying the normalized resource space onto peer-to-peer networks is proposed to obtain the advantages of P2P networks in managing large-scale dynamic network. The synergy of normalization and self-organization provides a solution to solve the problem of managing dynamic environment, large-scale decentralized, self-organized and complex resources.

The main theory, model and method of RSM was studied during 2001-2008. Publications have appeared in international journals since 2002. A systematic theory was published as monograph in 2008 (H.Zhuge, The Web Resource Space Model, Springer, 2008).

Related Notion: Faceted Classification

Typical Application: Faceted Browsing, Faceted Navigation, Faceted Exploration, and Faceted Search

Faceted navigation (also called faceted browsing and search) is an important approach to improving traditional web searching and browsing by refining the search results through a multi-step selection process. It allows users to view the contents of a set of resources from different facets.

The Resource Space Model naturally supports faceted navigation as the underlying resource organization model and theory due to its multi-dimensional classification characteristic.

Scholar search shows that the work published in (H. Zhuge, A knowledge grid model and platform for global knowledge sharing. Expert Systems Applications, 22(4)(2002)313-320) is the first faceted navigation system. The work published in the first edition of the book (H.Zhuge, The Knowledge Grid, World Scientific, 2004, chapter 3) is the first theoretical work on faceted browsing, navigation and search.

Fig.1 shows the interface for faceted browsing developed in 2001 (published in Expert Systems with Applications, 22(4)(2002)313-320). Fig.2 shows the interface for faceted browsing developed in 2003 (published in The Knowledge Grid, Chapter 4). Fig.3 shows the interface for faceted browsing developed in 2004-2005 (published in The Web Resource Space Model, Chapter 1).

Fig. 1

Fig. 2

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Special Issue

"Faceted Search, Interactive Semantics and Social Networking"， World Wide Web Journal (Call for Papers).

References

[1] H.Zhuge, The Complex Semantic Space Model, Keynote at 20th IEEE International Conference on Collaboration Technologies and Infrastructures, June 27th-29th, 2011, Paris, France (WETICE2011).

[2] H.Zhuge and Y.Xing, Probabilistic Resource Space Model fro Managing Resources in Cyber-Physical Society, IEEE Transactions on Service Computing, http://doi.ieeecomputersociety.org/10.1109/TSC.2011.12.

[3] H.Zhuge, The Web Resource Space Model, Springer, 2007.

[4] Jin Liu, X. Li, and L. Feng, Resource space view tour mechanism, Concurrency and Computation: Practice and Experience, 20(7)(2008) 863 - 883.

[5] H. Zhuge and X. Li, RSM-based Gossip on P2P Network, Keynote at ICA3PP2007.

[6] H.Zhuge, P.Shi, Y.Xing and C.He, Transformation from OWL Description to Resource Space Model, 1st Asian Semantic Web Conference, Beijing, China, Sept. 3-7, 2006. (Keynote), LNCS 4185, pp.4-23.

[7] H.Zhuge and E.Yao, Completeness of Query Operations on Resource Spaces, Proceedings of 2nd International Conference on Semantics, Knowledge and Grid, Guilin, China, November, 2006, IEEE Computer Society Press. (Keynote)

[8] H.Zhuge and Y.Xing, Integrity Theory for Resource Space Model and Its Application, The 6th International Conference on Web-Age Information Management (WAIM2005), Hangzhou, China, Oct.11-13, 2005. (Keynote), LNCS 3739, pp.8-24.

[9] H.Zhuge, E.Yao, Y.Xing, and J.Liu, Extended Normal Form Theory of Resource Space Model, Future Generation Computer Systems,21 (1) (2005) 189-198.

[10] H.Zhuge, The Knowledge Grid, World Scientific, Singapore, 2004.  (Chapter 2 discusses the normalization of semantic link network, chapter 3 discusses resource space model, and chapter 4 discusses the integration of the semantic link network and the resource space model to form a single semantic image.)

[11] H.Zhuge, Resource Space Grid: Model, Method and Platform, Concurrency and Computation: Practice and Experience, 16 (14) (2004) 1385 - 1413. 

[12] H.Zhuge, Fuzzy resource space model and platform. Journal of Systems and Software, 73(3)(2004)389-396.

[13] H.Zhuge, Resource Space Model, Its Design Method and Applications. Journal of Systems and Software, 72(1)(2004)71-81.

[14] H. Zhuge, A knowledge grid model and platform for global knowledge sharing. Expert Systems with Applications, 22(4)(2002)313-320.