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|Title: ||Management of contextual information to enhance mobile commerce applications : issues, framework, and approaches|
|Other Titles: ||Yong yu zeng qiang yi dong shang wu ying yong de huan jing zi xun guan li ji shu : wen ti, gou jia he fang fa tan tao|
用於增強移動商務應用的環境資訊管理技術 : 問題, 構架和方法探討
|Authors: ||Tang, Heng (唐恒)|
|Department: ||Department of Information Systems|
|Degree: ||Doctor of Philosophy|
|Issue Date: ||2008|
|Publisher: ||City University of Hong Kong|
|Subjects: ||Mobile commerce.|
Information resources management.
|Notes: ||CityU Call Number: HF5548.34 .T36 2008|
x, 156 leaves : ill. 30 cm.
Thesis (Ph.D.)--City University of Hong Kong, 2008.
Includes bibliographical references (leaves 144-156)
|Abstract: ||We are witnessing the tremendous growth in the adoption of mobile commerce
applications that strive to provide various services to mobile users. However, these
applications are plagued by the inherent hardware limitations of the mobile platforms.
In view of this problem, researchers and practitioners are now in attempt to utilize the
widely studied personalization techniques in mobile service recommendation because
personalization, which arranges products in coherence to individual user’s preference,
is acknowledged to be a prospective remedy. One of the biggest challenges in such
task is that conventional personalization techniques generally make decisions and
conduct reasoning based on historical demographic and preference information.
Therefore, nowadays’ personalization techniques have difficulties in reflecting the
dynamic aspects of a user on the move, and this situation motivates researchers to
incorporate user’s contextual information into mobile commerce applications.
However, primitive contextual information is hard to be directly used because of its
characteristics of being inaccurate and temporal. This dissertation addresses the issues
of managing contextual information by proposing a conceptual framework and
indicating necessary processes for transferring primitive contextual information into
usable knowledge. Towards this goal the framework adopts the process view of
Knowledge Management and proposes major processes of managing contextual
information, including collection, preprocessing, integration, modeling and
representation. The framework intends to enable the procedure of transforming data
and information to knowledge.
In addition, the dissertation identifies three important research problems in terms of the
preprocessing, modeling and utilizing contextual information, including: (i) similarity
search (ii) repetitive pattern discovery (iii) extracting rules and using for prediction.
For the first problem this dissertation presents a time series similarity measuring
approach for quantifying the relevance of two contextual scenarios characterized by
time series. Meanwhile, this approach effectively tackles the innate inaccuracy and
irregularity in primitive contextual time series. For the second problem, we propose a
pattern mining approach which outperforms conventional k-motif in that it does not
rely on the precise predefining of pattern length and it can aggregate underlying
patterns from extracted motifs. This method can be used to identify repetitive patterns
from user’s contextual time series. Regarding the third problem, we elaborate an
approach for predicting mobile user’s activity via the discovering, selecting and
matching of multidimensional sequential rules, which show much stronger prediction
ability than conventional single dimensional rules. The associated processes
(discovering, selecting and matching) can be viewed as a way of conducting
knowledge modeling and matching in the Context Information Management
Framework. These three proposed approaches are evaluated using both synthetic and
The proposed framework serves as a guideline for managing contextual information.
Furthermore, the proposed approaches constitute contributions to problems involving
temporal data, such as those arise in the enabling of context-awareness for real-world
mobile commerce application.|
|Online Catalog Link: ||http://lib.cityu.edu.hk/record=b2340571|
|Appears in Collections:||IS - Doctor of Philosophy |
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