Recommender System Using Collaborative Filtering Algorithm

With the vast amount of data that the world has nowadays, institutions are looking for more and more accurate ways of using this data. Companies like Amazon use their huge amounts of data to give recommendations for users. Based on similarities among items, systems can give predictions for a new item’s rating. Recommender systems use the user, item, and ratings information to predict how other users will like a particular item. Recommender systems are now pervasive and seek to make profit out of customers or successfully meet their needs. However, to reach this goal, systems need to parse a lot of data and collect information, sometimes from different resources, and predict how the user will like the product or item. The computation power needed is considerable. Also, companies try to avoid flooding customer mailboxes with hundreds of products each morning, thus they are looking for one email or text that will make the customer look and act. The motivation to do the project comes from my eagerness to learn website design and get a deep understanding of recommender systems. Applying machine learning dynamically is one of the goals that I set for myself and I wanted to go beyond that and verify my result. Thus, I had to use a large dataset to test the algorithm and compare each technique in terms of error rate. My experience with applying collaborative filtering helps me to understand that finding a solution is not enough, but to strive for a fast and ultimate one. In my case, testing my algorithm in a large data set required me to refine the coding strategy of the algorithm many times to speed the process. In this project, I have designed a website that uses different techniques for recommendations. User-based, Item-based, and Model-based approaches of collaborative filtering are what I have used. Every technique has its way of predicting the user rating for a new item based on existing users’ data. To evaluate each method, I used Movie Lens, an external data set of users, items, and ratings, and calculated the error rate using Mean Absolute Error Rate (MAE) and Root Mean Squared Error (RMSE). Finally, each method has its strengths and weaknesses that relate to the domain in which I am applying these methods

ROLE AND PLACE OF THE BRANCH SOCIAL DIALOGUE IN THE INDUSTRIAL RELATIONS OF MOLDOVA

Social dialogue as a very convenient tool for reconciling interests of key production factors – labour and capital – has been mentioned many times and on several other occasions. The present article reiterates this message, with social dialogue at sector level as a key subject under analysis. The interest lying at the basis of researches carried out on this matter was conditioned on one hand by the European Union requirements imposed on social dialogue at this level (the maturity of social partners at the level of industrial sectors impose a high rigor during the accession process of a country). On the other hand we are also keen to assess the respective maturity level in the case of the Republic of Moldova, its aspiration for the European integration being clear and indubitable.social dialogue, Trade Unions Collective Bargaining.

Training entrepreneurial culture in enterprises of the Republic of Moldova

This article addresses the problems related to the formation of organizational culture in the Republic of Moldova. There are reviewed the results of research carried out in the business of producing and conclusions that are made. It highlighted the role of human resources training in organizational culture. The paper highlights the preconditions for the creation of an entrepreneurial culture.Organization culture; Training; Entrepreneurial culture

pH-Mediated Regulation of Polymer Transport Through SiN Pores

We characterize the pH controlled polymer capture and transport thorough silicon nitride (SiN) pores subject to protonation. A charge regulation model able to reproduce the experimental zeta potential of SiN pores is coupled with electrohydrodynamic polymer transport equations. The formalism can quantitatively explain the experimentally observed non-monotonic pH dependence of avidin conductivity in terms of the interplay between the electroosmotic and electrophoretic drag forces on the protein. We also scrutinize the DNA conductivity of SiN pores. We show that in the low pH regime where the amphoteric pore is cationic, DNA-pore attraction acts as an electrostatic trap. This provides a favorable condition for fast polymer capture and extended translocation required for accurate polymer sequencing

MUSEUM CAGAR BUDAYA DAN EXHIBITION CENTER DI INDRAMAYU DENGAN KONSEP GREEN ARCHITECTURE

Perancangan ini mengacu kepada studi tentang pentingnya pemeliharaan cagar budaya dalam Undang – Undang Republik Indonesia No 11 Tahun 2010 Tentang Cagar Budaya, yang selanjutnya diikuti dengan Peraturan Pemerintah Tentang Museum No 66 Tahun 2015. Disamping itu, untuk penentuan dan pencarian lokasi yang strategis untuk perencanaan perancangan, maka perancangan juga terpacu pada Peraturan Daerah Kabupaten Indramayu No 1 Tahun 2012 Tentang Rencana Tata Ruang Wilayah Kabupaten Indramayu Tahun 2011 – 2031. Selain itu, perancangan diimbuhi dengan studi mengenai pengertian konsep museum dan cagar budaya ya dijelaskan di buku Pedoman Museum Cagar Budaya yang dikeluarkan oleh Direktorat Museum, Direktorat Jenderal Sejarah dan Purbakala Departemen Kebudayaan dan Pariwisata