Stephen Shaoyi Liao

Stephen Shaoyi Liao
City University of Hong Kong | CityU · Department of Information Systems

About

40
Publications
11,946
Reads
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1,217
Citations

Publications

Publications (40)
Article
Classical supervised machine learning techniques have been explored for semantically annotating unstructured textual data such as consumers' comments archived at social media websites to extract business intelligence. However, these techniques often require a large number of manually labeled training examples to produce accurate annotations. Severa...
Article
Recently, traffic jams and long queuing problems in tourist hot spots is growing with the increasing number of self-drive tourists. Some recommendation systems have been developed in attempt to relieve these problems. However, all these systems lack information pertaining to real-time traffic as well as the ability of personalization. In this resea...
Article
Effective knowledge integration plays a very important role in knowledge engineering and knowledge-based machine learning. The combination of Bayesian networks (BNs) has shown a promising technique in knowledge fusion and the way of combining BNs remains a challenging research topic. An effective method of BNs combination should not impose any part...
Article
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Personalized marketing via mobile devices, also known as Mobile Personalized Marketing (MPM), has become an increasingly important marketing tool because the ubiquity, interactivity and localization of mobile devices offers great potential for understanding customers' preferences and quickly advertising customized products or services. A tremendous...
Article
Full-text available
Sophisticated automatic incident detection (AID) technology plays a key role in contemporary transportation systems. Though many papers were devoted to study incident classification algorithms, few study investigated how to enhance feature representation of incidents to improve AID performance. In this paper, we propose to use an unsupervised featu...
Article
Full-text available
With the proliferation of its applications in various industries, sentiment analysis by using publicly available web data has become an active research area in text classification during these years. It is argued by researchers that semi-supervised learning is an effective approach to this problem since it is capable to mitigate the manual labeling...
Conference Paper
Full-text available
With the proliferation of its applications in various industries, sentiment analysis by using publicly available web data has become an active research area in text classification during these years. It is argued by researchers that semi-supervised learning is an effective approach to this problem since it is capable to mitigate the manual labeling...
Article
Full-text available
Continuous motorization and urbanization around the globe leads to an expansion of population in major cities. Therefore, ever-growing pressure imposed on the existing mass transit systems calls for a better technology, Intelligent Transportation Systems (ITS), to solve many new and demanding management issues. Many studies in the extant ITS litera...
Article
With competition intensifying in the globalized economy, an increasing number of firms are forming coalitions or alliances to improve purchasing efficiency and reduce operating costs in various industries. Forming such coalitions or alliances has become a key research challenge in two important kinds of decision support systems, namely group suppor...
Chapter
With the Web 2.0 paradigm, a huge volume of Web content is generated by users at online forums, wikis, blogs, and social networks, among others. These user-contributed contents include numerous user opinions regarding products, services, or political issues. Among these user opinions, certain comparison opinions exist, reflecting customer preferenc...
Conference Paper
Many organizations adopt information technologies to make intelligent decisions during operations. Time-series data plays a crucial role in supporting such decision making processes. Though current studies on time-series based decision making provide reasonably well results, the anomaly detection essence underling most of the scenarios and the plen...
Article
Competitive Intelligence is one of the key factors for enterprise risk management and decision support. However, the functions of Competitive Intelligence are often greatly restricted by the lack of sufficient information sources about the competitors. With the emergence of Web 2.0, the large numbers of customer-generated product reviews often cont...
Article
With the Web 2.0 paradigm, a huge volume of Web content is generated by users at online forums, wikis, blogs, and social networks, among others. These user-contributed contents include numerous user opinions regarding products, services, or political issues. Among these user opinions, certain comparison opinions exist, reflecting customer preferenc...
Conference Paper
Full-text available
Many information systems development companies are facing the question on how to apply agile methods in information systems maintenance (ISM). Performing correction of software defects in ISM inevitably degenerates program structure. On the other hand, agile methods provide refactoring to improve program structure without changing its behavior. Thi...
Conference Paper
With the increasing popularity of social networking sites and Web 2.0, people are building social relationships and expressing their opinions in the cyberspace. In this study, we introduce several novel methods to identify online communities with similar sentiments in online social networks. Our preliminary experiment on a real-world dataset demons...
Conference Paper
With the popularity of social networking sites (SNS) in this era of Web 2.0, increasingly more users are contributing their opinions about products and organizations. These online comments often have direct influence on consumers' buying decisions and the public's impressions of enterprises. As a result, enterprises have begun to use SNS to conduct...
Conference Paper
Because of the sheer volume of consumer reviews posted to the Internet, a manual approach for the detection and analysis of fake reviews is not practical. However, automated detection of fake reviews is a very challenging research problem given the fact that fake reviews could just look like legitimate reviews. Guided by the design science research...
Conference Paper
With the Web 2.0 paradigm, users play the active roles in producing Web contents at online forums, wiki, blogs, social networks, etc. Among these users contributed contents, many of them are opinions about products, services, or political issues. Accordingly, extracting the comparative relations about products or services by means of opinion mining...
Conference Paper
As much valuable domain knowledge is hidden in enterprises' text repositories (e.g., email archives, digital libraries, etc.), it is desirable to develop effective knowledge management tools to process this unstructured data so as to extract domain knowledge for business decision making. Ontology-based semantic annotation of documents is one of the...
Conference Paper
Current existing work on mining text data for business intelligence is not enough for many business applications, which need to analyze text data at fine grained level. The semantic annotation technology offers such potential functions, but current methods always suffer from a serious problem: requiring large mount of semantically annotated trainin...
Conference Paper
The recent growing interests in semantic Web trigger the requirements of annotating various information objects (e.g., documents) on the Web. The main drawback of the existing methods is that they usually require many manually annotated training examples as inputs. This paper proposes a SVM-struct based active learning algorithm for automatic seman...
Article
Finding previously unknown patterns in a time series has received much attention in recent years. Of the associated algorithms, the k-motif algorithm is one of the most effective and efficient. It is also widely used as a time series preprocessing routine for many other data mining tasks. However, the k-motif algorithm depends on the predefine of t...
Conference Paper
Full-text available
By analyzing historical data sequences and identifying relations between the occurring of data items and certain types of business events we have opportunities to gain insights into future status and thereby take action proactively. This paper proposes a new approach to cope with the problem of prediction on data sequence characterized by multiple...
Conference Paper
Ontology plays a crucial role in capturing and disseminating business information (e.g., products, services, relationships of businesses) for effective human computer interactions. However, manual construction of domain ontology is very labour intensive and time consuming. This paper illustrates a novel ontology population method for semi-automatic...
Conference Paper
This paper presents a novel clustering model for mining patterns from imprecise electric load time series. The model consists of three components. First, it contains a process that deals with representation and preprocessing of imprecise load time series. Second, it adopts a similarity metric that uses interval semantic separation (Interval SS)-bas...
Article
This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate....
Article
Full-text available
Providing personalized services for mobile commerce (m-commerce) can improve user satisfaction and merchant profits, which are important to the success of m-commerce. This paper proposes a Bayesian network (BN)-based framework for personalization in m-commerce applications. The framework helps to identify the target mobile users and to deliver rele...
Article
To achieve the full potential of mobile commerce (m-Commerce), many problems need to be resolved, such as how to make m-Commerce seamlessly span wide areas with heterogeneous information sources; how to improve the matchmaking between user requirements and product specifications; and how to make m-Commerce systems more intelligent in taking differe...
Article
Finding similar sequences in time series has received much attention and is a widely studied topic. Most existing approaches in the time series area focus on the efficiency of algorithms but seldom provide a means to handle imprecise data. In this paper, a more general approach is proposed to measure the distance of time sequences containing crisp...
Article
Full-text available
Context information plays an important role in context-aware mobile commerce (m-commerce) applications. Context information must be preprocessed, integrated and modelled before being stored and then used in a context-aware m-commerce application. Based on Knowledge Management (KM) theories and practice, this paper proposes a framework that uses sev...
Article
Most existing decision support systems (DSSs) are hard to fit satisfactorily into emerging working practices or organizational environments. Decision-making is becoming more pluralistic and less hierarchical, determined not so much by position in the corporate hierarchy but much by the argumentative and evidential value. Such decision-making can on...
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A society of intelligent agents can work together to monitor financial transactions and yield important information regarding potential financial calamities.
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Goal-oriented requirements analysis techniques provide ways to refine organizational and technical objectives, to more effectively explore alternatives during requirements definition. After selecting a set of alternatives to achieve these objectives, you can elaborate on them during subsequent phases to make them more precise and complete. The auth...
Article
Full-text available
The World Wide Web has become a rich information source from which answers to numerous questions can be found. However, there exist discrepancies between the queries by users and the answers provided by the information sources, due to ill-defined requirements and the irregular nature of Web information sources. Thus, the traditional rigid mechanism...
Article
Full-text available
Acquiring accurate and timely market share information is very important for producers to arrange producing plan and design marketing strategy. However the high cost and long period of collecting survey data in survey-based method make it much difficult to easily get latest market shares data. Recently, the emerging online web systems provide users...

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