Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline

Information Granulation for the Design of Granular Information Retrieval Systems

With the explosive growth of the amount of information stored on computer networks such as the Internet, it is increasingly more difficult for information seekers to retrieve relevant information. Traditional document ranking functions employed by Internet search engines can be enhanced to improve the effectiveness of information retrieval (IR). This paper illustrates the design and development of a granular IR system to facilitate domain specific search. In particular, a novel computational model is designed to rank documents according the searchers’ specific granularity requirements. The initial experiments confirm that our granular IR system outperforms a classical vector-based IR system. In addition, user-based evaluations also demonstrate that our granular IR system is effective when compared with a well-known Internet search engine. Our research work opens the door to the design and development of the next generation of Internet search engines to alleviate the problem of information overload

An Empirical Study of Online Consumer Review Spam: A Design Science Approach

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 methodology, one of the main contributions of our research work is the development of a novel methodology and an instantiation which can effectively detect untruthful consumer reviews. The results of our experiment confirm that the proposed methodology outperforms other well-known baseline methods for detecting untruthful reviews collected from amazon.com. Above all, the designed artifacts enable us to conduct an econometric analysis to examine the impact of fake reviews on product sales. To the best of our knowledge, this is the first empirical study conducted to analyze the economic impact of fake consumer reviews

A Preliminary Study on the Efficacy of a Community-Based Physical Activity Intervention on Physical Function-Related Risk Factors for Falls among Breast Cancer Survivors

Objective The aim of this study was to examine the effects of a 6-week community-based physical activity (PA) intervention on physical function-related risk factors for falls among 56 breast cancer survivors (BCS) who had completed treatments. Design This was a single-group longitudinal study. The multimodal PA intervention included aerobic, strengthening and balance components. Physical function outcomes based on the 4-meter walk, chair stand, one-leg stance, tandem walk, and dynamic muscular endurance tests were assessed at 6-week pre-intervention (T1), baseline (T2), and post-intervention (T3). T1-T2 and T2-T3 were the control and intervention periods, respectively. Results All outcomes, except the tandem walk test, significantly improved after the intervention period (p 0.05). Based on the falls risk criterion in the one-leg stance test, the proportion at risk for falls was significantly lower after the intervention period (p = 0.04), but not after the control period. Conclusions A community-based multimodal PA intervention for BCS may be efficacious in improving physical function-related risk factors for falls, and lowering the proportion of BCS at risk for falls based on specific physical function-related falls criteria. Further larger trials are needed to confirm these preliminary findings

Building Comparative Product Relation Maps by Mining Consumer Opinions on the Web

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 techniques could generate significant business values. From the producers’ perspective, they could better understand the relative strength or weakness of their products, and hence developing better products to meet the consumers’ requirements. From the consumers’ perspective, they could exercise more informed purchasing decisions by comparing the various features of certain kind of products. The main contribution of this paper is the development of a novel Support Vector Machine (SVM) based comparative relation map generation method for automatic product features analysis based on the sheer volume of consumer opinions posted on the Web. The proposed method has been empirically evaluated based on the consumer opinions crawled from the Web recently. Our initial experimental results show that the performance of the proposed method is promising, and the precision can achieve 73.15%

Enhancing Student Learning with Podcasting, a Newly Emergent Social Technology

The complement between pull and push learning modes is believed to be contributable to enriching students\u27 learning experiences. Podcasting, a push technology, can be used to push teaching materials to the students\u27 handheld devices, allowing them to study without any geographical and temporal constraints. The students can then revise the materials according to their own preferences. This explicit push technology together with students\u27 implicit pull motivation can encourage the students to learn in a more efficient way. As the students have the autonomy to choose their preferred media to access learning materials, it is believed to be able to increase students\u27 satisfaction in the learning process. We implemented this idea in one of the courses taught in a university in Hong Kong. The encouraging findings confirmed with our belief that podcasting can help students to learn better by increasing their learning satisfaction

About Bianchi I with VSL

In this paper we study how to attack, through different techniques, a perfect fluid Bianchi I model with variable G,c and Lambda, but taking into account the effects of a $c$-variable into the curvature tensor. We study the model under the assumption,div(T)=0. These tactics are: Lie groups method (LM), imposing a particular symmetry, self-similarity (SS), matter collineations (MC) and kinematical self-similarity (KSS). We compare both tactics since they are quite similar (symmetry principles). We arrive to the conclusion that the LM is too restrictive and brings us to get only the flat FRW solution. The SS, MC and KSS approaches bring us to obtain all the quantities depending on \int c(t)dt. Therefore, in order to study their behavior we impose some physical restrictions like for example the condition q<0 (accelerating universe). In this way we find that $c$ is a growing time function and Lambda is a decreasing time function whose sing depends on the equation of state, w, while the exponents of the scale factor must satisfy the conditions $\sum_{i=1}^{3}\alpha_{i}=1$ and $\sum_{i=1}^{3}\alpha_{i}^{2}<1,$ $\forall\omega$, i.e. for all equation of state$,$ relaxing in this way the Kasner conditions. The behavior of $G$ depends on two parameters, the equation of state $\omega$ and $\epsilon,$ a parameter that controls the behavior of $c(t),$ therefore $G$ may be growing or decreasing.We also show that through the Lie method, there is no difference between to study the field equations under the assumption of a $c-$var affecting to the curvature tensor which the other one where it is not considered such effects.Nevertheless, it is essential to consider such effects in the cases studied under the SS, MC, and KSS hypotheses.Comment: 29 pages, Revtex4, Accepted for publication in Astrophysics & Space Scienc

Five Dimensional Cosmological Models in General Relativity

A Five dimensional Kaluza-Klein space-time is considered in the presence of a perfect fluid source with variable G and $\Lambda$. An expanding universe is found by using a relation between the metric potential and an equation of state. The gravitational constant is found to decrease with time as $G \sim t^{-(1-\omega)}$ whereas the variation for the cosmological constant follows as $\Lambda \sim t^{-2}$, $\Lambda \sim (\dot R/R)^2$ and $\Lambda \sim \ddot R/R$ where $\omega$ is the equation of state parameter and $R$ is the scale factor.Comment: 13 pages, 4 figures, accepted in Int. J. Theor. Phy

Bianchi II with time varying constants. Self-similar approach

We study a perfect fluid Bianchi II models with time varying constants under the self-similarity approach. In the first of the studied model, we consider that only vary $G$ and $\Lambda.$ The obtained solution is more general that the obtained one for the classical solution since it is valid for an equation of state $\omega\in(-1,\infty)$ while in the classical solution $\omega\in(-1/3,1) .$ Taking into account the current observations, we conclude that $G$ must be a growing time function while $\Lambda$ is a positive decreasing function. In the second of the studied models we consider a variable speed of light (VSL). We obtain a similar solution as in the first model arriving to the conclusions that $c$ must be a growing time function if $\Lambda$ is a positive decreasing function.Comment: 10 pages. RevTeX