Trustworthy media news content retrieval from web using truth content discovery algorithm

Autor: Palaiyah Solainayagi, R. Ponnusamy
Rok vydání: 2019
Předmět:
Zdroj: Cognitive Systems Research. 56:26-35
ISSN: 1389-0417
DOI: 10.1016/j.cogsys.2019.01.002
Popis: Nowadays, the internet plays a major role in online information retrieval. As, we are well aware the web provides information related all the fields like national, lifestyle, movies, shopping, spirituality, sports, entertainment and much more. One cannot assume that the web retrieved information is believable or trustworthy due to multiple answers to the same query. The paper aims to study many research articles which are related to truth information discovery. However, the paper found that there is no proper research to find trustworthiness of news content which is extracted from multiple information sources with minimum misclassification error and retrieval time. To alleviate these issues, the truth content discovery algorithm is proposed to produce trustworthy information with minimal time along with multiple domain news information. The system provides reliable information from a various source of news provider with minimum classification error. The proposed method ranked the news content index based on query matches from extracted information. It minimizes the query retrieval time and classification error. Based on the experimental evaluation, proposed TCD + J48 algorithm produced the best result compared to existing approaches. It minimizes reduces 7.54 ms the query retrieval time (QRT), 5% Error rate (ER) and 0.98 and Mean Normalized Absolute Distance (MNAD).
Databáze: OpenAIRE