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Since the increased outsourcing and globalization of market competition demands, the designer needs more information when they are not in the office; this chapter will present a mobile semantic product information system that supports retrieveing and sharing product data among remote users. Semantic Web Technology has been utilized to provide semantic relationship and similarity of product data. The measure method of semantic similarity is proposed by taking advantage of the ISA relationship of concepts in ontology, which is shown by the experimental results that this method is efficient.

5.1 5.1 5.1 5.1 Introduction Introduction Introduction Introduction

Since the increased outsourcing and globalization of market competition, there is a demand for powerful web-based product information management system to support the representation, exchange, integration and sharing of product data over the internet. But, the traditional Product Data Management (PDM) system is difficult to describe the complex/underlying relation among the product data [21]; there are some disadvantages which cannot satisfy current requirements, such as:

� The search algorithm for traditional database is based on keywords searching, which cannot satisfy the high efficiency and complex requirements. Search results maybe lose some helpful information which is not indexed by the keywords. For the requirement of the mobile users, they need the return results

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more accurate because the small screen of the mobile device could not display a lot results and the connection fees could be expensive [7].

� Traditional database can not link all related information together to make the search result more appropriate to the user and easy to be managed. To overcome the limitations of traditional discovery models and improve discovery effectiveness, the emerging design guideline for novel discovery solutions is the adoption of semantic Web technology. Semantic Web technology permits explicit representation of interacting entities, e.g., services, resources and users, at a high level of abstraction while enabling automated reasoning about this representation, favouring interoperability and understanding between entities which have little or no prior knowledge about each other [57].

� The physical constraints of mobile devices, such as screen size, limited computational power and memory, which can significantly affect the usability of mobile applications link with traditional database, if the mobile user wants to retrieve some result via wireless network [46].

Therefore, in order to overcome the mentioned limitations and to deploy successful mobile applications in the distributed environment, following major tasks need to be focused on. Firstly, mobile client application should only ask for the minimum user input possible; secondly, the mobile system should resolve the user’s privacy concerns and enable further services by taking the personal input data. For example, the user may ask the system to recommend “standard bolt” for a private requirement.

In this case, the user may simply ask “find product bolt”; however, since “product bolt” in this context does not mean information about the supplier information of the bolt but rather material information for bolt, such as the CAD parametric data.

Conventional information system does not possess any intelligence to cooperate with database users. In order to meet the different requirement from users, system developers have to fully understand both the metadata and contents of the database.

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Even the users are familiar to the information system; they also have to retry specific queries repeatedly with alternative values until the query result is satisfactory. In order to overcome the limitations of current information system, new Semantic Information System need to be developed with following features:

� An information system needs to understand the schema and semantics of the database, it will be able to return informative responses and help the user input more correlated queries.

� A query language is used to obtain information from a database; and more user-friendly and fault-tolerant query interfaces will be developed. When a query search condition does not match with the underlying database, users would rather receive approximate answers than null information by relaxing the condition.

Thus, the Semantic Web Technology performs major implications in the development of new “semantic” information management recently; within this research field, ontology plays a key role for realizing the Semantic Web, which provides a common, shared understanding of knowledge in an interest domain;

capture and formalize knowledge by connecting human understanding of symbols with their machine process ability, and through the introduction of ontological reasoning, the approach are suitable for flexibly discovering abilities in using information, that were not specifically designed or intended for a particular use case [56].

Furthermore, semantic similarity (SS) approach is also introduced to make information system understand the schema and semantics of concepts and to measure the strength of similarity between data values [78, 79]. The value of SS can be used as a measure to determine the rank of each answer, which helps the users find useful information related to the input data. With the authors’ previous research in ontology

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construction and modelling in product design [6, 7], all the input data will be decided by their places in ontology tree and the return results will be assigned the value of semantic similarity; mobile semantic similarity information system utilizes the semantic similarity calculation method to provide a straightforward and efficient approach to rank the search results sorted by the value of SS. Another advantage of the knowledge system is that, the return result will not only show the information data property of the product, but people could find some underlying meaning; for example, if the user input “Bolt, the type is M12”, but the user maybe want to view the supplier’s information, or the other products which be provided by the same supplier. With the support from Ontology Reason Tools, such as Racer, Pellet etc, mobile system could resolve the problem by adding new ontology rules and do not needs to re-write the codes that make this system more robust and re-usable.