درخت حوزه‌های تخصصی

Recommender systems are important tools for users to identify their preferred items and for businesses to improve their products and services. In recent years, the use of online services for selection and reservation of hotels have witnessed a booming growth. Customer’ reviews have replaced the word of mouth marketing, but searching hotels based on user priorities is more time-consuming. This study is aimed at designing a recommender system based on the explicit and implicit preferences of the customers in order to increase prediction’s accuracy. In this study, we have combined sentiment analysis with the Collaborative Filtering (CF) based on deep learning for user groups in order to increase system accuracy. The proposed system uses Natural Language Processing (NLP) and supervised classification approach to analyze sentiments and extract implicit features. In order to design the recommender system, the Singular Value Decomposition (SVD) was used to improve scalability. The results show that our proposed method improves CF performance.

The heavy trends of the Information Society are knowledge that requires the spirit of innovation, creativity, flexibility and critical thinking “more than benign introspection.” In addition, information about each other’s relationships with oneself, the other and the environment is crucial to enable individuals to understand the complex reality. The Moroccan school is part of this societal vision, by renovating its education and training programs, which claim the development of the quality of procedural, cognitive and metacognitive strategies. In this perspective this research work aimed at studying the engineering analysis of investigation approaches in the teaching of SVT for the implementation of a reflexive practice in lycian learners, generating the ability to process information and invest in mechanisms for understanding, conceptualizing and proceduralizing cognitive and metacognitive strategies. Informational investigative capacity is crucial because it informs learning decisions, which can lead to innovations in the delivery of cognitive styles. To do this, we chose to conduct our study, through interview surveys and semi-structured questionnaires. The first among teachers and the second for SVT inspectors from three provincial directorates of National Education. The results show that the majority of those involved in education are involved in the classical informational approach and the experimental approach. The use of investigative analysis approaches remains episodic in some learning units (scientific ecological output and DNA extraction). Teachers are keen to introduce new information technologies to create favourable conditions for learning about investigative approaches, in order to improve the power of analysis, treatment and critical thinking and coping with situations of authentic and novel learning. We are concerned about the ability to understand what and how each of its actors is further shaping.

The purpose of this study was to investigate the effect of scenario planning on strategic innovation considering the mediating role of strategic thinking and strategic flexibility. This research is applied in terms of purpose and descriptive survey in nature. The statistical population of the study is the manufacturing companies of Bushehr province. In order to determine the sample size, the test-software method (G-Power) was used. Based on this, 222 observations were calculated. Using a simple random sampling method with the online survey, 176 questionnaires were finally received by the researchers. Data analysis was performed using the structural equation method and Smart PLS 3 software. Research findings showed that scenario planning has a positive and significant effect on strategic innovation. The mediating effect of strategic flexibility and strategic thinking in the relationship between scenario planning and strategic innovation is also significant. The present study expands the management literature by filling in research gaps. Organizations today need to change their past strategies to be able to understand and meet customer needs faster and more competitively than other competitors.

Profit is one of the most important factors influencing economic decision making, the changes of which depend on various factors. Banks, as one of the most important business units, have a special reliance on the concept of profitability and their performance is significantly influenced by macroeconomic conditions. Government economic policies are placed. This paper aims at applying the panel regression model to study the effect of monetary policy on the profitability of banks from 2006 to 2018 using data from 30 provinces to find appropriate policy recommendations for decision-making in the banking system. The research method was the use of GMM regression technique in the context of combined data. According to the results, the performance and profitability of banks are improved by the implementation of expansionary monetary policy. However, bank lending and price inflation have a negative effect on banks' performance. According to the results of this study, control variables such as the amount of overdue claims and GDP also had a positive effect on the performance of banks. Also at the macro level, with regard to the negative effects of Expansion monetary policy and the growth of liquidity, with the controlled implementation of Expansion monetary policy, it helps to improve the performance of banks in the banking system.