Multiple Criteria Neuro housing mining

The research aims at developing a method and system for Multiple Criteria Neuro Housing Mining. Multiple Criteria Neuro Housing Mining comprises the following components: Sentiment analysis, Neuro-mining and Recommender decision support system. Below is a brief analysis of the system’s components.

Sentiment analysis, quantitative and qualitative research methodologies

With Sentiment analysis, we are able to routinely identify sentiments expressed in articles, reviews, surveys, comments, sentiments, notices, papers, research, studies, blogs, online forums, Facebook, Twitter and other social media channels, thereby allowing visualisation of sentiments residents hold towards issues of housing, which would take into account different micro-environment (pollution, noise, intrinsic life goals, lifestyle behaviors, life-long learning, social relations, social support, self-development, community involvement, relationships), the meso-environment (socioeconomic features of the area, infrastructure, etc.) and the macro-environment (economic, environmental, technological, legal, political, social, cultural, religious, ethnic, ethical and equality aspects as well as gender and values) factors. We use dictionaries of keywords to classify documents (articles, reviews, surveys, comments, sentiments, notices, papers, research, studies, online forums or other social media channels) as positive, neutral or negative. By applying Sentiment analysis we can understand and monitor thoughts, sentiments, attitudes, emotions and preferences of residents better and allow business and municipalities to make superior tips on sustainability for the housing challenge best practices used. Sentiment analysis will summarize sentiments of residents from a range of social media channels and identify sustainable housing trends. Sentiment analysis can help cities measure and understand the housing challenge sentiments on key housing issues better.

In order to evaluate the current housing situation, various quantitative (based on socio-economic and other criteria) and qualitative (based on ethnographic researches and case studies, pro-forma questionnaires and comparative analysis social media and review sites) research methodologies will be used.

Neuro-mining using remote biometrics (face, voice, thermo, heart rate and blood pressure analysis) techniques

Neuro-mining analyses the housing sustainability taking into account the resident’s valence, arousal and emotional state. Neuro-mining will rate housing according to the resident’s valence, arousal and emotional state (pleasure, displeasure, etc.) and develops emotional map of housing.

Recommender decision support system

Recommender decision support system will analyse different quantitative and qualitative micro-environment (pollution, noise, intrinsic life goals, lifestyle behaviors, life-long learning, social relations, social support, self-development, community involvement, relationships), the meso-environment (socioeconomic features of the area, infrastructure, etc.) and the macro-environment (economic, environmental, technological, legal, political, social, cultural, religious, ethnic, ethical and equality aspects as well as gender and values) factors, directly or indirectly, influencing on housing sustainability performance. Recommender decision support system will behave like a human consultant: supporting residents, business and municipalities by analysing housing, identifying and diagnosing problems, proposing possible courses of action (refurbishment of buildings, effective management of the public spaces, attract residents, businesses, students, tourists, cultural operators and events, etc.) and evaluating such proposed actions.