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Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries
( Carlos Porcel ),( Alberto Ching-lpez ),( Juan Bernabe-moreno ),( Alvaro Tejeda-lorente ),( Enrique Herrera-viedma ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.4
The significant advances in information and communication technologies are changing the process of how information is accessed. The internet is a very important source of information and it influences the development of other media. Furthermore, the growth of digital content is a big problem for academic digital libraries, so that similar tools can be applied in this scope to provide users with access to the information. Given the importance of this, we have reviewed and analyzed several proposals that improve the processes of disseminating information in these university digital libraries and that promote access to information of interest. These proposals manage to adapt a user`s access to information according to his or her needs and preferences. As seen in the literature one of the techniques with the best results, is the application of recommender systems. These are tools whose objective is to evaluate and filter the vast amount of digital information that is accessible online in order to help users in their processes of accessing information. In particular, we are focused on the analysis of the fuzzy linguistic recommender systems (i.e., recommender systems that use fuzzy linguistic modeling tools to manage the user`s preferences and the uncertainty of the system in a qualitative way). Thus, in this work, we analyzed some proposals based on fuzzy linguistic recommender systems to help researchers, students, and teachers access resources of interest and thus, improve and complement the services provided by academic digital libraries.
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Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries
Porcel, Carlos,Ching-Lopez, Alberto,Bernabe-Moreno, Juan,Tejeda-Lorente, Alvaro,Herrera-Viedma, Enrique Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.4
The significant advances in information and communication technologies are changing the process of how information is accessed. The internet is a very important source of information and it influences the development of other media. Furthermore, the growth of digital content is a big problem for academic digital libraries, so that similar tools can be applied in this scope to provide users with access to the information. Given the importance of this, we have reviewed and analyzed several proposals that improve the processes of disseminating information in these university digital libraries and that promote access to information of interest. These proposals manage to adapt a user's access to information according to his or her needs and preferences. As seen in the literature one of the techniques with the best results, is the application of recommender systems. These are tools whose objective is to evaluate and filter the vast amount of digital information that is accessible online in order to help users in their processes of accessing information. In particular, we are focused on the analysis of the fuzzy linguistic recommender systems (i.e., recommender systems that use fuzzy linguistic modeling tools to manage the user's preferences and the uncertainty of the system in a qualitative way). Thus, in this work, we analyzed some proposals based on fuzzy linguistic recommender systems to help researchers, students, and teachers access resources of interest and thus, improve and complement the services provided by academic digital libraries.
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Gonzalez-Herrera, A.L.,Salgado-Bernabe, M.,Velazquez-Velazquez, C.K.,Salcedo-Vargas, M.,Andrade-Manzano, A.,Avila-Moreno, F.,Pina-Sanchez, P. Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.4
Background: Cervical cancer (CeCa) is the second most common cancer in women in developing countries, and human papilloma virus (HPV) is the primary etiological factor. Aberrant expression of HOX transcription factors has been observed in several types of cancer. To date, however, no reports exist on the expression of HOXB2 and HOXB13 proteins during neoplastic progression in CeCa and its correlation with HPV infection. Materials and Methods: Expression of HOXB2 and HOXB13 proteins was assessed in tissue microarrays from normal cervical epithelium, cervical intraepithelial neoplasias grade 1-3, and CeCa. HPV was detected by PCR and sequencing. Expression of HOX-positive cells was determined in each diagnostic group. Results: Percentage of HOXB2- and HOXB13-positive cells gradually increased from means of 10.9% and 16.7%, respectively, in samples from healthy women, to 75.2% and 88.6% in those from CeCa patients. Frequency of HPV infection also increased from 13% in healthy tissue samples to 92.3% in CeCa. Both HOXB2 and HOXB13 proteins were preferentially expressed in HPV+ samples. Conclusions: The present study represents the first report on the expression of both HOXB2 and HOXB13 proteins through cervix tumorigenesis, providing evidence that increased expression of such proteins is a common event during progression to CeCa.
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