Journal of Information Science recent issues

The role of knowledge management in achieving effective crisis management: a case study

Wang, W.-T., Belardo, S. — Mon, 23 Nov 2009 06:35:10 PST

While most would agree that effective knowledge management can improve the management of crises, it is surprising how little research has been done in this area. In order to begin to address this deficiency, this study presents a framework designed to determine whether, and to what extent, knowledge management can positively impact crisis management (CM). The framework is the result of combining classic strategic CM frameworks with Zack’s knowledge strategy framework. A case study of two energy companies in Taiwan is conducted to investigate the relationships between knowledge strategies and critical CM factors. The research results indicate two main findings. First, an organization needs to employ different knowledge strategies at different phases of a business crisis to fulfil its different knowledge needs and achieve the desired CM outcomes. Second, there are significant relationships among knowledge strategies, crisis phases, and crisis characteristics, as summarized in nine theoretical propositions.

Online use and information seeking behaviour: institutional and subject comparisons of UK researchers

Nicholas, D., Clark, D., Rowlands, I., Jamali, H. R. — Mon, 23 Nov 2009 06:35:10 PST

The paper reports on the results of the project ‘Evaluating the usage and impact of e-journals in the UK’. Using deep log analysis techniques, we evaluated the use of the Oxford Journals database in regard to life sciences, economics and history by 10 major UK research institutions. The aim of the study was to investigate researchers’ digital behaviour, and to ascertain whether it varied by subjects and disciplines, or in relation to the institutions. The findings revealed significant subject and institutional differences. Life scientists were the biggest users. Economists made the greatest use of abstracts. Historians proved to be the most active searchers. Research intensive universities were characterized by high volume use and short session times, light sessions, and sessions which utilized few of the search functions available. Open access journals featured strongly in the ranked lists of life sciences and history; and Google was an extremely popular means of accessing journal content, especially so in the case of historians.

Mining sequential patterns in the B2B environment

Hu, Y.-H., Chen, Y.-L., Tang, K. — Mon, 23 Nov 2009 06:35:10 PST

Sequential pattern mining is a powerful data mining technique for finding time-related behaviour in sequence databases. In this paper, we focus on mining sequential patterns in the business-to-business (B2B) environment. Because customers’ sequences in the B2B environment are very long, and almost all items are frequently purchased by all customers, using traditional methods may result in a large number of uninteresting and meaningless patterns and a long computational time. To solve these problems, we introduce three conditions (constraints) — compactness, repetition, and recency — and consider them jointly with frequency in selecting sequential patterns. An efficient algorithm is developed to discover frequent sequential patterns which satisfy the conditions. Empirical results show that the proposed method is computationally efficient and effective in extracting useful sequential patterns in the B2B environment.

Ecological framework of information interactions and information infrastructures

Huvila, I. — Mon, 23 Nov 2009 06:35:10 PST

There has been notably little convergence between information organization and information use studies. A framework for explicating the contextual interplay of information interactions and infrastructures of information, and more specifically the interface of information work and knowledge organization systems, is proposed. The theoretical foundations of the framework are based on systems theory and ecological approach. It is suggested that the interplay of information use and information infrastructures may be conceptualized as a systemic interaction, which is driven by the simultaneous influence of human activity related warrants and infrastructural affordances and constraints. The model provides an instrument that explicates the interplay of human information use and information infrastructures.

Effectiveness of web search results for genre and sentiment classification

Na, J.-C., Thet, T. T. — Mon, 23 Nov 2009 06:35:10 PST

The motivation of this study is to enhance general topical search with a sentiment-based one where the search results (snippets) returned by the web search engine are clustered by sentiment categories. Firstly we developed an automatic method to identify product review documents using the snippets (summary information that includes the URL, title, and summary text), which is genre classification. Then the identified snippets were automatically classified into positive (recommended) and negative (non-recommended) documents, which is sentiment classification. Thereafter the user may directly decide to access the positive or negative review documents. In this study we used only the snippets rather than their original full-text documents, and applied a common machine learning technique, SVM (support vector machine), and heuristic approaches to investigate how effectively the snippets can be used for genre and sentiment classification. The results show that the web search engine should improve the quality of the snippets especially for opinionated documents (i.e. review documents).

Dublin Core metadata semantics: an analysis of the perspectives of information professionals

Park, J.-r., Childress, E. — Mon, 23 Nov 2009 06:35:10 PST

This study examines Dublin Core (DC) metadata semantics drawn from the perspectives and experiences of cataloguing and metadata professionals. The study ascertains the extent of difficulty in applying the DC metadata elements encountered by these professionals and examines factors engendering such difficulties during the metadata application process. Comments drawn from the survey participants (n = 141) show that conceptual ambiguities (41%) and semantic overlaps (45%) of the surveyed DC metadata elements are the most frequently cited factors causing difficulty and confusion, in turn leading to variant interpretations of DC metadata elements. This has the potential to bring forth inconsistent and inaccurate applications and implementation of the DC standard across institutions which can directly affect semantic interoperability across digital repositories. The high degree of difficulty (55.3%) engendered by the Relation field indicates that further examination of this element is needed.

Online communities of practice typology revisited

Hara, N., Shachaf, P., Stoerger, S. — Mon, 23 Nov 2009 06:35:10 PST

This paper outlines a typology for online communities of practice. The typology is based on findings from observations of three online communities of practice, a content analysis of messages, and a review of the existing literature. The three examples of communities of practice are of electronic discussion lists that cover topics of interest to university webmasters, librarians, and educators. This work expands on a typology that consolidated prior research and focused on online communities of practice within organizational settings by extending it to be inclusive of open online communities of practice that are not constrained by any organizational context. Characterizing communities of practice in this manner enables various aspects of them to be analysed, which can illuminate ways to support the implementation of effective online communities of practice for specific purposes.

Crowdsourcing, attention and productivity

Huberman, B. A., Romero, D. M., Wu, F. — Mon, 23 Nov 2009 06:35:10 PST

We show through an analysis of a massive data set from YouTube that the productivity exhibited in crowdsourcing exhibits a strong positive dependence on attention, measured by the number of downloads. Conversely, a lack of attention leads to a decrease in the number of videos uploaded and the consequent drop in productivity, which in many cases asymptotes to no uploads whatsoever. Moreover, short-term contributors compare their performance to the average contributor’s performance while long-term contributors compare it to their own media.

Google stemming mechanisms

Uyar, A. — Tue, 15 Sep 2009 07:50:41 PDT

In this study we investigated the stemming mechanisms of Google. We used its web interface and submitted many queries via a program. Stemming is the process of correlating morphologically similar words with one another. Search engines use stemming to match documents having one form of a word with queries having another form of the same word. We investigated the stemming mechanism of Google for three classes of words: singulars/plurals, combined words, and verbs with many postfixes. Our results indicate that Google uses a document-based algorithm for stemming. It evaluates each document separately and makes a decision to index or not for the conflated forms of the words it has. It indexes documents only for word forms that are semantically strongly correlated. While it indexes documents for singulars and plurals frequently, it rarely indexes documents for word forms with the postfixes of -able or -tively.

Ubiquitous city: Urban technologies, urban infrastructure and urban informatics

Shin, D.-H. — Tue, 15 Sep 2009 07:50:41 PDT

South Korea continues to lead the way in digital opportunity with its recent, innovative and ubiquitous city projects. The u-city initiative in South Korea is a national urban development project that focuses on strengthening the role of information and communication technologies in civic planning and management. This study tracks the changing dynamics driving the information society initiative of South Korea to evaluate the process of design and development of u-city. This study reviews qualitative data related to the u-city projects, describes the transformations and translation of this data in the public, political, and social discourse, and discusses the prospectus of a ubiquitous information society environment. The findings raise fundamental, practical questions about the role of ubiquitous computing in shaping our future cities. The findings show that there are more challenges ahead than prospects, despite the fact that the u-city has all the advanced technological components for a positive development. The South Korean u-city is typically more prone to problems related to the lack of social infrastructure, market restrictions, political quagmires and vested financial interests. The paper discusses the deficiencies of the South Korean approach, namely a lack of holistic approach by integrating technological possibilities with social application needs.

Moderating effects of task characteristics on information source use: An individual-level analysis of R&D professionals in new product development

Bin, G. — Tue, 15 Sep 2009 07:50:41 PDT

Through an individual-level analysis of R&D professionals in technology-based firms, the current study examines the moderating effects of task characteristics on the relationships between source characteristics and information source use in terms of use frequency and source internality, in the context of new product development. The results show that task characteristics moderate the effects of source characteristics on information source use. Specifically, task uncertainty moderates the effect of source accessibility on use frequency for both internal and external sources. The positive relationship between source accessibility and use frequency of information sources is stronger when task uncertainty is low than when it is high. Furthermore, the results reveal that task characteristics moderate the effects of source characteristics on source internality. The present study provides strong evidence that the key to understanding how task characteristics affect information source use and reconciling the disagreements between the least effort principle and the quality-driven perspective is to examine the moderating effects of task characteristics on information seeking behaviour, and take into account the potential substitution effect between internal and external sources in information seeking.

Ontologies for crisis contagion management in financial institutions

Ye, K., Wang, S., Yan, J., Wang, H., Miao, B. — Tue, 15 Sep 2009 07:50:41 PDT

What makes crisis management in financial institutions fairly unique and particularly complex is the accompanying crisis contagion or systemic risk. The subprime mortgage crisis currently happening in the USA is a typical example. In order to further deepen our understanding of how crisis contagion occurs and enhance information interchange and knowledge sharing among related entities, ontologies for crisis contagion management in financial institutions are proposed in this study. Three categories of ontologies, which include static ontology, dynamic ontology, and social ontology, are developed to deal with different perspectives in this domain. The three types of ontology are then united in the Ontology Web Language (OWL) and the Semantic Web Rules Languages (SWRL) framework, both of which are machine readable. Finally, the case of Long-Term Capital Management (LTCM) is offered to demonstrate how the proposed ontologies are used in financial institutions.

Automated document metadata extraction

Adefowoke Ojokoh, B., Sunday Adewale, O., Oluwole Falaki, S. — Tue, 15 Sep 2009 07:50:42 PDT

Web documents are available in various forms, most of which do not carry additional semantics. This paper presents a model for general document metadata extraction. The model, which combines segmentation by keywords and pattern matching techniques, was implemented using PHP, MySQL, JavaScript and HTML. The system was tested with 40 randomly selected PDF documents (mainly theses). An evaluation of the system was done using standard criteria measures namely precision, recall, accuracy and F-measure. The results show that the model is relatively effective for the task of metadata extraction, especially for theses and dissertations. A combination of machine learning with these rule-based methods will be explored in the future for better results.

A relational data harmonization approach to XML

Niemi, T., Nappila, T., Jarvelin, K. — Tue, 15 Sep 2009 07:50:42 PDT

There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.

The {pi}-index: a new indicator for assessing scientific impact

Vinkler, P. — Tue, 15 Sep 2009 07:50:42 PDT

There are several simple and sophisticated scientometric indicators generally applied in the literature (e.g. total number of publications and citations, citations per journal paper, relative citedness indexes, Hirsch index, etc.), which may characterize the publications of scientists both qualitatively and quantitatively. The calculation methods generally use data referring to the total set of papers studied. Scientific progress, however, may be attributed primarily to information in the highly cited publications. Therefore, a new indicator (-index) is suggested for comparative assessment of scientists active in similar subject fields. The -index is equal to one hundredth of the number of citations obtained to the top square root of the total number of journal papers (‘elite set of papers’) ranked by the decreasing number of citations. The relation of the -index to other indexes and its dependence on the field is studied, using data of journal papers of ‘highly cited researchers’.

Disciplinary differences in the use of internet discussion groups: differential communication needs or trust problems?

Matzat, U. — Tue, 15 Sep 2009 07:50:42 PDT

This paper tests empirically the claim that the successful application of information and communication technologies (ICTs) depends on the social context of their use. There are striking differences in the prevalence of ICT use between researchers in different academic disciplines. Nevertheless it is unclear whether and how they depend on disciplinary differences of the academic communication system. This paper presents several existing and new hypotheses that specify how disciplinary differences in communication systems influence whether researchers make use of so-called internet discussion groups (IDGs). The hypotheses either argue that specific trust problems inhibit IDG subscription or that IDGs fulfil discipline-specific communication needs, which gives incentives for subscription. They are tested with data of a sample of university researchers in the natural and social sciences and the humanities. The trust hypotheses are not confirmed. The idea that IDGs have a distinct orientation function that diminishes deficiencies in the existing communication systems of some disciplines finds support. Scholars who work in research fields that are difficult to overview, that is fields with a high number of journals, have a special incentive to subscribe to IDGs.

An empirical comparison of ontology matching techniques

Alasoud, A., Haarslev, V., Shiri, N. — Fri, 10 Jul 2009 04:10:21 PDT

Ontology matching aims to find semantic correspondences between a pair of input ontologies. A number of matching techniques have been proposed recently. We may, however, benefit more from a combination of such techniques as opposed to just a single method. This is more appropriate, but very often the user has no prior knowledge about which technique is more suitable for the task at hand, and it remains a labour intensive and expensive task to perform. Further, the complexity of the matching process as well as the quality of the result is affected by the choice of the applied matching techniques. We study this problem and propose a framework for finding suitable matches. A main feature of this is that it improves the structure matching techniques and the end result accordingly. We have developed a running prototype of the proposed framework and conducted experiments to compare our results with existing techniques. While being comparable in efficiency, the experimental results indicate our proposed technique produces better quality matches.

Receiving the French: a bibliometric snapshot of the impact of `French theory' on information studies

Cronin, B., Meho, L. I. — Fri, 10 Jul 2009 04:10:21 PDT

This study explores the extent to which `French theory' (Bourdieu, Derrida, Foucault et al.) has left its mark on the scholarly literature of information studies. A bibliometric analysis reveals which theorists (and which works) have been most highly cited over the course of the last four decades. The study also identifies the information studies journals and scholars who have been the most frequent citers of French theorists.

Simulation study of the inventory effect of the scientific paper publishing process

Guang Yu, , Li, Y.-J., Yu, D.-R. — Fri, 10 Jul 2009 04:10:21 PDT

By simulating the change process of the inventory of scientific papers according to a mathematical model of the publishing process, we find that publication delay would cause statistical error of the scientific paper output indicator, i.e. the quantity of published papers. Based on a simulation model and the average publication delay, we construct an optimization algorithm of the actual scientific paper output using a nonlinear least squares algorithm and validate its accuracy. To simplify the solution process, we propose an approximate algorithm of the actual scientific paper output indicator which would help science and technology managers practically deduce an approximation of the actual indicator. This has implications for strategy decision making and allocation of resources for science and technology research by policy makers.

A fuzzy biclustering algorithm for social annotations

Lixin Han, , Hong Yan, — Fri, 10 Jul 2009 04:10:21 PDT

In recent years, there has been considerable interest in the analysis of social annotations. Social annotations allow users to annotate web resources more easily, openly and freely than do taxonomies and ontologies. In this paper, we propose a novel algorithm for social annotations. It introduces a fuzzy biclustering algorithm to social annotations for identifying subgroups of users and of resources, and discovering the relationships between those users for social annotations. The algorithm employs a combination of pattern search and compromise programming to construct hierarchically structured biclusters. The pattern search method is used to compute a single objective optimal solution, and the compromise programming is used to trade-off between multiple objectives. The algorithm is not subject to the convexity limitations, and does not need to use the derivative information. It can automatically identify user communities and achieve high prediction accuracies.

Articulating complex information needs using query templates

Vechtomova, O., Hao Zhang, — Fri, 10 Jul 2009 04:10:21 PDT

In this paper we investigate the effectiveness of topic-independent query templates as a tool for assisting users in articulating their information needs. We hypothesize that topic-independent query templates can help users with complex information needs to express their requirements more accurately and in greater detail. We developed a set of query templates representing general semantic relationships between concepts, such as cause—effect and problem—solution. Each template was written in the form of a fill-in-the-blanks question. A user study was performed comparing the template-based interface with a single-textbox search interface. Results demonstrate that, while users found the template-based query formulation less easy to use, the queries written using templates performed better than the queries written using the control interface with one query textbox.

Informational uses of spiritual information: an analysis of messages reportedly transmitted by extraphysical means

Kari, J. — Fri, 10 Jul 2009 04:10:21 PDT

This article explores informational uses of spiritual information presented in spiritual publications. Informational use entails cognitive or communicational activity that — on the basis of information — focuses on representations of the perceived existence, whereas practical use of information centres on tangible — material or energetic — activities of the real world. Some earlier research has been done on the informational uses of information, but spiritual information has been ignored almost altogether in this context. The empirical work was grounded on a representative sample of spiritual texts. The method of analysing the data was inductive content analysis. The main result of this study was the discovery and dissection of three fundamental varieties of informational information use: internalizing information, processing knowledge, and externalizing knowledge. The classification constructed in this study can be seen as a useful tool for further investigation into information use, but it should be refined in subsequent research.

Investigation of the accuracy of search engine hit counts

Uyar, A. — Fri, 10 Jul 2009 04:10:21 PDT

This study investigates the accuracy of search engine hit counts for search queries. We investigate the accuracy of hit counts for Google, Yahoo and Microsoft Live Search, and the accuracy of single and multiple term queries. In addition, we investigate the consistency of hit count estimates for 15 days. The results show that all three provide estimates for the number of matching documents and the estimation patterns of their counting algorithms differ greatly. The accuracy of hit counts for multiple word queries has not been studied before. The results of our study show that the number of words in queries affects the accuracy of estimations significantly. The percentages of accurate hit count estimations are reduced almost by half when going from single word to two word query tests in all three search engines. With the increase in the number of query words, the error in estimation increases and the number of accurate estimations decreases.

Translation disambiguation for cross-language information retrieval using context-based translation probability

Kishida, K., Ishita, E. — Fri, 10 Jul 2009 04:10:21 PDT

Disambiguation between multiple translation choices is very important in dictionary-based cross-language information retrieval. In prior work, disambiguation techniques have used term co-occurrence statistics from the collection being searched. Experimentally these techniques have worked well but are based upon heuristic assumptions. In this paper, a theoretically grounded alternative is proposed, one which uses sense disambiguation based upon context terms within the source text. Specifically this paper introduces the concept of translation probabilities incorporating a context term and extends the IBM Model 1 for estimating context-based translation probabilities from a sentence-aligned bilingual corpus. Experimental results in English to Italian bilingual searches show significant performance improvement of the context-based translation probabilities over the case without any disambiguation.

Erratum

Thu, 05 Nov 2009 07:47:11 PST

Aardvark et al.: Quality journals and gamesmanship in management studies, Journal of Information Science first published on July 12, 2007 as DOI: 10.1177/0165551506077419. This version is no longer available. The version of record is published in Vol. 33 No. 6, DOI: 10.1177/0165551507077419.

Eliciting conceptual models to support interdisciplinary research

Beers, P. J., Bots, P. W.G. — Thu, 07 May 2009 06:10:27 PDT

Constructing interdisciplinary knowledge is particularly difficult because scientific knowledge is situated in its discipline. Researchers must find common ground to share, and this causes high transaction costs. This article reports a method of conceptual analysis to elicit, analyse and compare conceptual models used by individual researchers, with the ultimate aim to facilitate researchers in sharing these models. Using this method, an analyst derives concepts and their mutual relations from documents, and defines them in natural language. We qualitatively analysed all writings of four researchers from an interdisciplinary research project and validated the resulting conceptual models in semi-structured interviews. The method was found to be effective in eliciting concepts, even those used implicitly. The interviews also revealed mechanisms by which researchers adopt new concepts or choose particular terms. The analysis costs are high but not prohibitive, and are shown to diminish with each researcher added to the analysis.

Understanding the sustainability of a virtual community: model development and empirical test

Cheung, C. M.K., Lee, M. K.O. — Thu, 07 May 2009 06:10:27 PDT

With the proliferation of Web 2.0 technologies, there is an expanded opportunity for individuals to get involved in information exchange. In this study, the sustainability of a virtual community for teachers and educators were investigated. The research model borrows the key concepts from the IS continuance model, social influence theory, the uses and gratifications paradigm, and relationship marketing to explain user intention to continue using a virtual community, as well as intention to recommend the community to others. Satisfaction, commitment, group norms are found to have significant impacts on intention to continue using and intention to recommend. Among the three factors, satisfaction has the highest impact on behavioral intentions. Individual-related factors (purposive value and self-discovery) are found to have significant impacts on user satisfaction, while social-related factors are more important in determining commitment and group norms. The results of this study provide important implications for both research and practice.

Analysis of terrorist social networks with fractal views

Yang, C. C., Sageman, M. — Thu, 07 May 2009 06:10:27 PDT

Social network visualization has drawn significant attention over recent years. It creates images of social networks that provide investigators with new insights about network structures and helps them to communicate those insights to others. Visualization facilitates the social network analysis. It supports the investigators to discover patterns of interactions among the social actors including detecting subgroups, identifying central actors and their roles, and discovering patterns of interactions among social actors. However, visualizing a large heterogeneous social network has several challenges. The large size of networks, complex relations among social actors and limited number of available pixels on a screen make it difficult to present important information clearly to investigators and hence reduce the capability of investigators to explore the networks. In this work, we propose the fractal views to construct a visual abstraction of a large and complex social network with users selected social actors as focuses. The fractal views are focus and context visualization techniques using an information reduction approach. It controls the amount of information displayed by focusing on the syntactic structure of information. It is useful in discovering knowledge from terrorist social networks for combating the war on terrorism. Such application has formed an important research topic, known as intelligence and security informatics, in recent years due to the terrorist attacks of September 11 2001 (9/11) and several other terror attacks that have occurred within the last decade. We present several case studies to demonstrate the capability of the proposed technique on analyzing the Global Salafi Jihad terrorist social network. It extracts the hidden relationships among terrorists through user interactions. In addition, we have conducted a user evaluation to assess the efficiency and effectiveness of fractal views. It shows that fractal views outperform fisheye views and zoom-in windows to support users in visualizing and analyzing terrorist social networks.

An evaluation framework of user interaction with metadata surrogates

Balatsoukas, P., Morris, A., O'Brien, A. — Thu, 07 May 2009 06:10:27 PDT

This paper proposes a framework for the evaluation of user interaction with textual metadata surrogates in the search result interfaces of various types of Information Retrieval (IR) systems. Metadata surrogates are representations of the full-text documents displayed to the user as a list of retrieved results after a search has been performed in an IR system. By examining the metadata surrogates, users can make judgments about the relevance of the full-text document without having to access and evaluate the document itself, thus saving a considerable amount of time and effort. The literature review, however, reveals a lack of frameworks for the evaluation of users' interaction with metadata surrogates. The implications of such a framework would be to inform designers and researchers of IR systems about the main components of users' interaction with metadata surrogates and to facilitate the process of evaluating metadata surrogates in terms of content and presentation.

Social tagging, online communication, and Peircean semiotics: a conceptual framework

Huang, A. W.-C., Chuang, T.-R. — Thu, 07 May 2009 06:10:27 PDT

One of the recent web developments has focused on the opportunities it presents for social tagging through user participation and collaboration. As a result, social tagging has changed the traditional online communication process. The interpretation of tagging between humans and machines may create new problems if essential questions about how social tagging corresponds to online communications, what objects the tags refer to, who the interpreters are, and why they are engaged are not explored systematically. Since such reasoning is an interpretation of social tagging among humans, tags and machines, it is a complex issue that calls for deep reflection. In this paper, we investigate the relevance of the potential problems raised by social tagging through the framework of C.S. Peirce's semiotics. We find that general phenomena of social tagging can be well classified by Peirce's 10 classes of signs for reasoning. This suggests that regarding social tagging as a sign and systematically analyzing the interpretation are positively associated with the 10 classes of signs. Peircean semiotics can be used to examine the dynamics and determinants of tagging; hence, the various uses of this categorization schema may have implications for the design and development of information systems and web applications.

A new sampling technique for association rule mining

Mahafzah, B. A., Al-Badarneh, A. F., Zakaria, M. Z. — Thu, 07 May 2009 06:10:27 PDT

Association Rule Mining (ARM) is one of the data mining techniques used to extract hidden knowledge from datasets, that can be used by an organization's decision makers to improve overall profit. However, performing ARM requires repeated passes over the entire database. Obviously, for large database, the role of input/output overhead in scanning the database is very significant. A popular solution to improve the speed of ARM is to apply the mining algorithm on a sample instead of the entire database. In this paper, a parameterized sampling algorithm for ARM is presented. This algorithm extracts sample datasets based on three parameters: transaction frequency, transaction length and transaction frequency-length. To evaluate its performance and accuracy, a comparison against a two-phase sampling-based algorithm is performed using real and synthetic datasets. The experimental results show that the proposed sampling algorithm in some cases outperforms two-phase sampling algorithm, and achieves up to 98% accuracy.