Abstract: Feature extraction plays an important role in face recognition system as it can reduce dimensions and reserve the most significant features which need to be classified and recognized. Principal Component Analysis (PCA) has been one of the popular techniques that used in pattern recognition related research areas. Researches have been also carried out to improve the performance of this technique, mainly based on tensor type and incremental type. Incremental Bi-Directional Principal Component Analysis (IBDPCA) is one of the latest improved versions of PCA which combined the merits from tensor and incremental type. However, IBDPCA lacks of the moderations between the latest and previous data when updating the means. This can leads to difficulty in evaluating the data accurately due to larger size of previous data, and also more memory waste. This paper proposed a technique which overcomes the limitations by adopting the IBDPCA with forgetting factors, in order to down-weight the previous

• Publication Date: 11-Aug-2012
• DOI: 10.15224/978-981-07-3161-8-255
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Abstract: This paper aims to equip the next generation of Web users with the idea of personalized presentation of Web contents by substituting some of the real Web contents with the `Virtual Web Contents' (VWC). In order to realize this idea, we introduce a novel concept of Personal Conceptual Dictionary (PCD). The PCD is an ontology-based dictionary of a collection of user-defined concepts that is utilized to create a new personalized layer of VWC residing between the real web contents and the end-user. Hence, the end-users rather than interacting with all the real contents, may also interact with some of the `Virtual Web Contents' creating an exciting environment making their data visualization more personal and browsing more flexible. Our hypothesis is that by integrating VWC with real Web contents, the Web of future will not just work different but also provides more personalized and pleasant experience to its users. We present some interesting results obtained from the initial implementatio

• Publication Date: 11-Aug-2012
• DOI: 10.15224/978-981-07-3161-8-908
• Views: 0
• Downloads: 0