HOTEL RECOMMENDATION SYSTEM BASED ON REVIEW AND CONTEXT INFORMATION: A COLLABORATIVE FILTERING APPRO

In most organizations, knowledge sharing is often lacking when it comes to business systems success. This paper investigates factors affecting business systems success in Saudi organisations. Data were collected from private organisations in Saudi Arabia and Partial Least Square approach has been applied to analyse the data. The results show that organisational culture influence knowledge sharing towards business systems success. In addition, both intrinsic motivation and perceived usefulness has positive influence on business system success. This indicates that business system success is built upon the concept of knowledge sharing and user motivation

Matrix Factorization Techniques for Context-Aware Collaborative Filtering Recommender Systems: A Survey

open access articleCollaborative Filtering Recommender Systems predict user preferences for online information, products or services by learning from past user-item relationships. A predominant approach to Collaborative Filtering is Neighborhood-based, where a user-item preference rating is computed from ratings of similar items and/or users. This approach encounters data sparsity and scalability limitations as the volume of accessible information and the active users continue to grow leading to performance degradation, poor quality recommendations and inaccurate predictions. Despite these drawbacks, the problem of information overload has led to great interests in personalization techniques. The incorporation of context information and Matrix and Tensor Factorization techniques have proved to be a promising solution to some of these challenges. We conducted a focused review of literature in the areas of Context-aware Recommender Systems utilizing Matrix Factorization approaches. This survey paper presents a detailed literature review of Context-aware Recommender Systems and approaches to improving performance for large scale datasets and the impact of incorporating contextual information on the quality and accuracy of the recommendation. The results of this survey can be used as a basic reference for improving and optimizing existing Context-aware Collaborative Filtering based Recommender Systems. The main contribution of this paper is a survey of Matrix Factorization techniques for Context-aware Collaborative Filtering Recommender Systems

Tourist experiences recommender system based on emotion recognition with wearable data

The collection of physiological data from people has been facilitated due to the mass use of cheap wearable devices. Although the accuracy is low compared to specialized healthcare devices, these can be widely applied in other contexts. This study proposes the architecture for a tourist experiences recommender system (TERS) based on the user’s emotional states who wear these devices. The issue lies in detecting emotion from Heart Rate (HR) measurements obtained from these wearables. Unlike most state-of-the-art studies, which have elicited emotions in controlled experiments and with high-accuracy sensors, this research’s challenge consisted of emotion recognition (ER) in the daily life context of users based on the gathering of HR data. Furthermore, an objective was to generate the tourist recommendation considering the emotional state of the device wearer. The method used comprises three main phases: The first was the collection of HR measurements and labeling emotions through mobile applications. The second was emotional detection using deep learning algorithms. The final phase was the design and validation of the TERS-ER. In this way, a dataset of HR measurements labeled with emotions was obtained as results. Among the different algorithms tested for ER, the hybrid model of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks had promising results. Moreover, concerning TERS, Collaborative Filtering (CF) using CNN showed better performance.This research was financially supported by the Ministry of Science, Technology, and Innovation of Colombia (733-2015) and by the Universidad Santo Tomás Seccional Tunja. We thank the members of the GICAC group (Research Group in Administrative and Accounting Sciences) of the Universidad Santo Tomás Seccional Tunja for their participation in the experimental phase of this investigation

Learning Opportunities 2009/2010

The graduation requirements of the Illinois Mathematics and Science Academy are in concert with those maintained by the State of Illinois with additional requirements as established by the IMSA Board of Trustees. Each semester students must take a minimum of 2.5 credits and a maximum of 3.5 credits. One-semester classes generally receive .5 credits and two semester classes (e.g., World Languages) generally receive 1.0 credit. Most students will take between 5 and 7 academic classes per semester. Fine Arts, Wellness, and Independent Study courses do not count towards the 2.5 credit minimum. However, if a student wishes to take 3.5 credits of academic classes, he/she may choose to enroll in a Fine Arts or Independent Study course on a Pass/Fail basis (see below)

Embedding Graphs under Centrality Constraints for Network Visualization

Visual rendering of graphs is a key task in the mapping of complex network data. Although most graph drawing algorithms emphasize aesthetic appeal, certain applications such as travel-time maps place more importance on visualization of structural network properties. The present paper advocates two graph embedding approaches with centrality considerations to comply with node hierarchy. The problem is formulated first as one of constrained multi-dimensional scaling (MDS), and it is solved via block coordinate descent iterations with successive approximations and guaranteed convergence to a KKT point. In addition, a regularization term enforcing graph smoothness is incorporated with the goal of reducing edge crossings. A second approach leverages the locally-linear embedding (LLE) algorithm which assumes that the graph encodes data sampled from a low-dimensional manifold. Closed-form solutions to the resulting centrality-constrained optimization problems are determined yielding meaningful embeddings. Experimental results demonstrate the efficacy of both approaches, especially for visualizing large networks on the order of thousands of nodes.Comment: Submitted to IEEE Transactions on Visualization and Computer Graphic

Visitor Management at UNWHS: A Case study of Taj Mahal

Studies have shown a significant increase in the number of visitors to the site after being featured on the UNWHS list which leads to visitation pressure and impacts thereof on the site. Visitor management at the UNWHS is the need of the hour. The paper aims to critically analyse the existing visitor management plan at the selected UNWHS - Taj Mahal, the second-best UNWHS in the world with more than 8 million visitors every year (timesofindia.indiatimes.com, tribuneindia.com, indiatoday. in, hindustantimes.com, 2017), and to suggest numerous proactive and reactive measures to bring about an effective Visitor Management strategy for the Site. The descriptive and exploratory research methodology has been used along with a mixed approach of both Quantitative and Qualitative Methods. Literature review of Visitor Management practices followed at UNWHS globally and an in-depth study of opinion of different groups – Site Managers, Travel agents, Guides, Visitors visiting the site helped conclude, that to defy the harmful impact of the visitation and to give an enhanced experience, an effective marketing plan with strict conservation and preservation practices have to be implemented in collaboration with locals, stakeholders and the government agencie

The relation between the music festival brand equity and the intention to visit the host city: the cases of Eurovision & NOS Alive in Lisbon

Festivals, and events in general, increase the appeal of tourism, motivating people to visit the host cities. Literature shows the influence music festivals have on tourism, but not how it impacts a permanent vs. an occasional event differently. The research questions are: Is different the impact of the festival on the host city, according to be a permanent or occasional one? Does each festival brand equity influence the host city tourism? For the first time ever, Lisbon hosted the Eurovision Song Festival, an annual festival which is hosted by a different country each year. NOS Alive is a famous music Festival held in Lisbon every year. This study aims to understand the visitors’ profile, their motivation and visiting patterns, as well as to analyze the impact of these mega festivals on tourism in Lisbon. A unique questionnaire was designed and submitted to a convenient sample of each festival’s international participants. The research model defines six comparative hypotheses for both Festivals using the Pearson correlation coefficient. and the relationships among the model constructs are different according to the festival type, i.e, occasional vs permanent festivals. One hypothesis was not confirmed for both Festivals, H2: “Host city familiarity is related to the attachment to the host city”. Two hypotheses were partially verified for both festivals: H1: “Festival brand equity is related to the attachment to the host city”; H5: “The attachment to the host city is related to the intention to visit the city”.Festivais, e eventos em geral, aumentam a atratividade do turismo, motivando as pessoas a visitar as cidades que os recebem. A literatura existente mostra a influencia dos festivais de música no turismo, mas não a diferença desse impacto relacionando um festival permanente com um ocasional. As questões de pesquisa são: Será diferente o impacto do festival na cidade que o recebe, consoante é permanente ou ocasional? Será que o seu brand equity influencia o turismo na cidade que o recebe? Pela 1ª vez, Lisboa recebeu o festival da Eurovisão, um festival ocasional, realizado a cada ano num país diferente. O NOS Alive, é um famoso festival de música que acontece em Lisboa, todos os anos. Este estudo pretende perceber o perfil dos visitantes, as suas motivações e os padrões de visita e assim, analisar o impacto destes mega festivais no turismo de Lisboa. Um único questionário foi criado e submetido aos participantes estrangeiros de cada festival. Comparando os festivais, seis hipóteses se definiram e se testaram pelo coeficiente de correlação de Pearson. Em geral, os resultados são diferentes para cada festival, diferindo a relação entre o modelo de constructos e o tipo de festival, ocasional vs. permanente. Uma hipótese não é verificada para os dois festivais, a H2: “A familiaridade com a cidade de destino está relacionada com a ligação à cidade de destino”. Duas hipóteses são parcialmente verificadas para os dois festivais: H1: “O brand equity do festival está relacionado com a ligação à cidade de destino”; H5 “A ligação à cidade de destino está relacionada com a intenção de visitar a cidade”