Finding products and items in large online space that meet the user needs is difficult. Users may spend a considerable amount of time before finding item relevant to their needs. Like many other economic branches, growing Internet usage also change user behavior in the real-estate market. Advancement in virtual reality offers a virtual tour, interactive maps, floor plans that make an online rental website popular among users. With an abundance of information, recommender systems become more than ever important to suggest the user with relevant property and reduce search time. A sophisticated recommender in this domain can assist the need of a real-estate agent. Session-based user behavior, lack of user profile leads to the use of traditional recommendation methods. In this research, we proposed an approach for real-estate recommendation based on Gated Orthogonal Recurrent Unit (GORU) and Weighted Cosine Similarity. GORU captures the user searching context and weighted cosine similarity improves the rank of pertinent property. To conduct this research, we have used the data of an online public real estate web portal 4. The factual data represents the original behavior of the user on an online portal. We have used Recall, User coverage and Mean Reciprocal Rank (MRR) metric for the evaluation of our system against other state-of-the-art techniques. Proposed solution outperforms various baselines and state-of-the-art RNN based solutions.
The present study explored the relationship of emotional intelligence and psychological distress with internet addiction. The participants were 200 individuals from different universities of Islamabad and Rawalpindi, who were active internet users in their daily life. A co-relational method was used in order to obtain the quantitative analysis of the relationship between the three variables. The Internet Addiction Test (Young, 1998), Wong and Law Emotional Intelligence Scale (Wong et al., 2007) and the Depression Anxiety Stress Scale-21were used. The results supported the hypothesis that there is a relationship between internet addiction, psychological distress and emotional intelligence among internet users.
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