Combining collaborative and content-based filtering to recommend research papers

The number of research papers available today is growing at a staggering rate, generating a huge amount of information that people cannot keep up with. According to a tendency indicated by the United States’ National Science Foundation, more than 10 million new papers will be published in the next 20 years. Because most of these papers will be available on the Web, this research focus on exploring issues on recommending research papers to users, in order to directly lead users to papers of their interest. Recommender systems are used to recommend items to users among a huge stream of available items, according to users’ interests. This research focuses on the two most prevalent techniques to date, namely Content-Based Filtering and Collaborative Filtering. The first explores the text of the paper itself, recommending items similar in content to the ones the user has rated in the past. The second explores the citation web existing among papers. As these two techniques have complementary advantages, we explored hybrid approaches to recommending research papers. We created standalone and hybrid versions of algorithms and evaluated them through both offline experiments on a database of 102,295 papers, and an online experiment with 110 users. Our results show that the two techniques can be successfully combined to recommend papers. The coverage is also increased at the level of 100% in the hybrid algorithms. In addition, we found that different algorithms are more suitable for recommending different kinds of papers. Finally, we verified that users’ research experience influences the way users perceive recommendations. In parallel, we found that there are no significant differences in recommending papers for users from different countries. However, our results showed that users’ interacting with a research paper Recommender Systems are much happier when the interface is presented in the user’s native language, regardless the language that the papers are written. Therefore, an interface should be tailored to the user’s mother language.

Percepção de coerção em pacientes psiquiátricos, cirúrgicos e clínicos hospitalizados

Duzentos e cinco pacientes hospitalizados em um grande hospital universitário foram avaliados, em estudo transversal, para a identificação de sentimentos de coerção no momento da hospitalização. A amostra compunha-se de 64 pacientes psiquiátricos, 58 pacientes cirúrgicos e 83 pacientes clínicos, tanto involuntários, quanto voluntários. A voluntariedade dos pacientes psiquiátricos foi determinada por seu status legal e, a dos cirúrgicos e clínicos, pelo caráter eletivo ou emergencial da hospitalização. Os pacientes psiquiátricos eram mais jovens, apresentavam nível educacional mais elevado e escores superiores na escala SRQ em relação aos pacientes cirúrgicos e clínicos. Esses grupos não diferiam entre si no que se refere aos escores em MMSE. O Admission Experience Survey: Short Form e as escalas utilizadas durante o MacArthur Coercion Study, foram aplicados a todos os pacientes. Os resultados indicam que os pacientes psiquiátricos, tanto involuntários quanto voluntários, apresentam significativamente maior percepção de coerção do que os demais. Os pacientes cirúrgicos e clínicos não diferem entre si, entretanto referem haver sofrido também algum nível de coerção, fato que poderia merecer uma atenção maior de bioeticistas e juristas. A análise de regressão logística indica que as variáveis associadas a hospitalização involuntária são Perceived Coercion Scale, estado cognitivo e escolaridade, todas com coeficiente de correlação positivo.