Danny Chiang Choon Poo

A context-based investigation into source use by information seekers

An important question in information-seeking behavior is where people go for information and why information seekers prefer to use one source type rather than another when faced with an information-seeking task or need for information. Prior studies have paid little attention to contingent variables that could change the cost-benefit calculus in source use. They also defined source use in one way or the other, or considered source use as a monolithic construct. Through an empirical survey of 352 working professionals in Singapore, this study carried out a context-based investigation into source use by information seekers. Different measures of source use have been incorporated, and various contextual variables that could affect the use of source types have been identified. The findings suggest that source quality and access difficulty are important antecedents of source use, regardless of the source type. Moreover, seekers place more weight on source quality when the task is important. Other contextual factors, however, are generally less important to source use. Seekers also demonstrate a strong pecking order in the use of source types, with online information and face-to-face being the two most preferred types.

A hybrid approach for user profiling

With the growing amount of information being digitized, users find it difficult to obtain the most relevant information that is hidden in the deluge of information returned to them by search engines. In this paper, we describe a conceptual model using a hybrid approach based on user profiling approaches and information filtering techniques that can alleviate the problem of information overload. We discuss the concepts, namely static content profiling, static collaborative profiling, dynamic content profiling and dynamic collaborative profiling, followed by the design and implementation of a library search facility, which has employed these concepts. Preliminary experiments conducted have shown that users have benefited from our prototype system. It appears that there is value in employing these new concepts that we have proposed in the design and implementation of future information retrieval system for better retrieval.

An expert system approach to online catalog subject searching

Abstract The various ways of improving the online catalog for subject searching are reviewed. The paper then discusses the expert system approach to developing a subject search front-end. It is suggested that an effective expert front-end can be developed by focusing on search strategies. A design for a rule-based expert system front-end is described. Possible search strategies and selection rules are illustrated. The inference structure of the system is based on Clanceys model of heuristic classification.

Capturing tacit knowledge across different domains: Knowledge Community (K-Comm)

Capturing tacit knowledge is one of the major challenges faced by Knowledge Management Systems (KMS). Most such systems try to capture employee knowledge pertaining to a specific domain of organisational interest. However, every employee has much more to contribute apart from knowledge in a particular area. The sum total of his/her skills, interests and experiences make for rich knowledge. Our research focuses on maximising the knowledge potential of every employee across different domains. We have developed a system to identify an individuals knowledge areas, based on his/her strengths, experiences and passion. It will enable an individual to contribute and share knowledge with other individuals. When applied to the organisation, it should help increase the span of knowledge areas reachable by KMS, and make them more effective. We move from a scenario where there are few experts towards one where everyone is an expert, and has something to share.

Java Database Connectivity

Applications that require complex manipulation of data will need to use a database to store information. Many Java applications fall into this category. Although many database vendors provide Java APIs, they are proprietary to their database implementations. Therefore, it becomes very difficult to port applications from one database to another. Java Database Connectivity (JDBC) APIs provide a simplified and uniform access to the database management systems from different vendors. In this chapter you will learn the essential classes and techniques to use JDBC APIs.

Detecting and supporting known item queries in online public access catalogs

When users seek to find specific resources in a digital library, they often use the library catalog to locate them. These catalog queries are defined as known item queries. As known item queries search for specific resources, it is important to manage them differently from other search types, such as area searches. We study how to identify known item queries in the context of a large academic institutions online public access catalog (OPAC), in which queries are issued via a simple keyword interface. We also examine how to recognize when a known item query has retrieved the item in question. Our approach combines techniques in machine learning, language modeling and machine translation evaluation metrics to build a classifier capable of distinguishing known item queries and correctly classifies titles for whether they are the known item sought with an 80% and 95% correlation to human performance, respectively on each task. To our knowledge, this is the first report of such work, which has the potential to streamline the user interface of both OPACs and digital libraries in support of known item searches

An evolutionary structural model for software maintenance

Abstract The traditional approach to business information system development, in which development and maintenance are regarded as separate and distinct phases, has placed overemphasis on a pragmatic but artificial distinction between these phases. This article is concerned with an approach to software development in which delivered systems are regarded as evolutionary products and, as such, have a seamless split between initial development and subsequent refinement. To achieve this requires a clearer separation between the business policies, functional requirements, and object models that are conventionally embedded into software, often in a way that makes their identification difficult. Thus maintenance, and hence evolution, are also difficult.

Aspect-Based Twitter Sentiment Classification

Due to the popularity of Twitter, sentiment classification for Twitter has become a hot research topic. Previous studies have approached the problem as a tweet-level classification task where each tweet is classified as positive, negative or neutral. However, getting an overall sentiment might not be useful to organizations which are using twitter for monitoring consumer opinion of their products/services. Instead, it is more useful to determine specifically which aspects of the products/services the users are happy or unhappy about. This paper proposes an aspect-based sentiment classification approach to analyze sentiments for tweets. To the best of our knowledge, we are the first to perform sentiment analysis for Twitter in this manner. We conducted several experiments and show that by incorporating results from the aspect-based sentiment classifier, we are able to improve existing tweet-level classifiers. The experimental results also demonstrated that our approach outperforms existing state-of-the-art approaches.

Design and implementation of the E-referencer

Abstract An expert system Web interface to online catalogs called E-Referencer is being developed. An initial prototype has been implemented. The interface has a repertoire of initial search strategies and reformulation strategies that it selects and implements to help users retrieve relevant records. It uses the Z39.50 protocol to access library systems on the Internet. This paper describes the design and implementation of the E-Referencer. A preliminary evaluation of the strategies is also presented.

E-Referencer: A Prototype Expert System Web Interface to Online Catalogs

An expert system Web interface to online catalogs called E-Referencer is being developed. An initial prototype has been implemented. The interface has a repertoire of initial search strategies and reformulation strategies that it selects and implements to help users retrieve relevant records. It uses the Z39.50 protocol to access library systems on the Internet. This paper describes the design of E-Referencer, and the development of search strategies to be used by the interface. A preliminary evaluation of the strategies is also presented.