8638055
Function-Based Analysis of an Electronic Commerce Website
Traditionally, studies with the technology acceptance model (TAM) have treated software systems as holistic units. A survey is conducted to understand the model better by dropping from system-wide measurement to function-based measurement. The first part of the survey replicates Gefen and Straub’s (2000) study where only intention is measured at the function level, with consistent results. System-wide perceived ease of use (PEOU) has more effect on an intrinsic task (intention to search for books) than on an extrinsic task (intention to purchase books). In the second part of the survey, all factors are measured at the function level. The result shows that the function-level models are more predictive than the system-wide model. Specifically, each PEOU is a significant predictor for each intention in both models. This study shows the value of using function-based analysis and suggests that function-based analysis is particularly useful and timely for the study of integrated products offering relatively distinct functions.
18442431
Understanding the Balanced Effects of Belief and Feeling on Information Systems Continuance
There are innumerable studies on technology adoption as well as continuance of usage. A review of previous research shows that cognitive factors are considered prominently in information technology adoption and continuance while the affective feelings of users are not. Although attitude and user satisfaction are common factors considered in information systems research, these factors only involve partial aspects of feelings. Researchers in the marketing areas, as well as the psychology area, begin to note the importance of feelings in understanding and predicting human and customer behavior. In many modern applications, such as mobile Internet services, user feelings are expected to be important, since users are not just technology users but also service consumers. Drawing upon the support of consumer research, social psychology, and computer science, this study proposes a balanced belief–feeling model of IS continuance. In the process of developing this model, the concepts of attitude, belief, and feelings are further articulated, defined, and distinguished. The balanced model is tested in a survey of mobile Internet users. The results established the validity of the model. A comparison with the IS continuance model shows that the new model can explain significantly more variance in continuance intention, taking into account that the new model has more factors. We offer theoretical reasoning for the balanced effects of belief and feeling on IS continuance and discuss the theoretical and practical implications of this study.
1880699
A distance measure for bounding probabilistic belief change
We propose a distance measure between two probability distributions, which allows one to bound the amount of belief change that occurs when moving from one distribution to another. We contrast the proposed measure with some well known measures, including KL-divergence, showing how they fail to be the basis for bounding belief change as is done using the proposed measure. We then present two practical applications of the proposed distance measure: sensitivity analysis in belief networks and probabilistic belief revision. We show how the distance measure can be easily computed in these applications, and then use it to bound global belief changes that result from either the perturbation of local conditional beliefs or the accommodation of soft evidence. Finally, we show that two well known techniques in sensitivity analysis and belief revision correspond to the minimization of our proposed distance measure and, hence, can be shown to be optimal from that viewpoint.
8031191
Dynamic dictionary matching and compressed suffix trees
Recent breakthrough in compressed indexing data structures has reduced the space for indexing a text (or a collection of texts) of length <i>n</i> from <i>O</i>(<i>n</i> log <i>n</i>) bits to <i>O</i>(<i>n</i>) bits, while allowing very efficient pattern matching [10, 13]. Yet the compressed nature of such indices also makes them difficult to update dynamically. This paper presents the first <i>O</i>(<i>n</i>)-bit representation of a suffix tree for a dynamic collection of texts whose total length is <i>n</i>, which supports insertion and deletion of a text <i>T</i> in <i>O</i>(|<i>T</i> | log<sup>2</sup> <i>n</i>) time, as well as all suffix tree traversal operations, including forward and backward suffix links. This work can be regarded as a generalization of the compressed representation of static texts. Our new suffix tree representation serves as a core part in a compact solution for the dynamic dictionary matching problem, i.e., providing an <i>O</i>(<i>d</i>)-bit data structure for a dynamic collection of patterns of total length <i>d</i> that can support the dictionary matching query efficiently. When compared with the <i>O</i>(<i>d</i> log <i>d</i>)-bit suffix tree based solution of Amir <i>et al.</i>, the compact solution increases the query time by roughly a factor of log <i>d</i> only. In the study of the above results, we also derive the first <i>O</i>(<i>n</i>)-bit representation for maintaining <i>n</i> pairs of balanced parentheses in <i>O</i>(log <i>n</i>/log log <i>n</i>) time per operation, matching the time complexity of the previous <i>O</i>(<i>n</i> log <i>n</i>)-bit solution.
19601656
A mutation-sensitive approach for locating conserved gene pairs between related species
This paper proposes a new approach for solving the whole genome alignment problem. Our approach is based on a new structural optimization problem (called the MUM selection problem) related to mutations via reversals and transpositions. We have devised a practical algorithm for this optimization problem and have evaluated the algorithm using 15 pairs of human and mouse chromosomes. The results show that our algorithm is both effective and efficient. More specifically, our algorithm can reveal 91% of the conserved gene pairs that have been reported in the literature. When compared to existing software MUMmer and MaxMinCluster , our algorithm uncovers 15% and 7% more genes on average, respectively. The sensitivity of our algorithm is also slightly higher. The paper concludes with a remark on the computational hardness of the MUM selection problem.
2565301
Visualizing input and output analysis for simulation (VINOAS)
Abstract Input analysis which involves a large amount of statistical analysis is one of the major steps in simulation. A software package with a well-designed user-friendly graphical window interface has been developed to assist modelers in identifying the underlying statistical distribution of the input data. It integrates techniques for assessing sample independence, hypothesizing families of distributions, estimation of parameters, and performing goodness-of-fit tests in a graphical environment. This allows the modelers to use the package in an interactive way and efforts can be saved in specifying the input probability distribution.
257219
On the Revision of Probabilistic Beliefs using Uncertain Evidence
We revisit the problem of revising probabilistic beliefs using uncertain evidence, and report results on several major issues relating to this problem: how should one specify uncertain evidence? How should one revise a probability distribution? How should one interpret informal evidential statements? Should, and do, iterated belief revisions commute? And what guarantees can be offered on the amount of belief change induced by a particular revision? Our discussion is focused on two main methods for probabilistic revision: Jeffrey's rule of probability kinematics and Pearl's method of virtual evidence, where we analyze and unify these methods from the perspective of the questions posed above.