Abstract
The abundance of information prohibits getting relevant results on online social researches. Thus, RSS feeds appear as monitoring tool of current events according to users preferences. However, the user is flooded by the amount of such RSS feeds. For that reason, any analysis of RSS feeds seems effortful and complex. In this paper, we aim to improve the effectiveness and swiftness of pertinent RSS feeds analysis through recommending suitable fragments of queries during the analysis process of events. Accordingly, we propose an innovative architecture of our new active RSS feeds warehouse. Additionally, we introduce a new recommender system to improve the querying expression of RSS feeds. Our experiment results show the robustness and efficiency of our approach.
Highlights
IntroductionThe need to provide pertinent results on information retrieval proliferates
The social media is becoming increasingly popular
We proposed a new active data warehouse architecture involved by two dedicated layers
Summary
The need to provide pertinent results on information retrieval proliferates In this context, really simple syndication (RSS). According to Inmon [15], the data warehouse is an integrated collection of subject oriented, nonvolatile, historized, summarized and available data for analysis. Such data are organized according to analysis subjects in order to facilitate the extraction of relevant information. In such a context, OLAP operations can be performed in data warehouse to assist the decision maker [14]. The assistance of the analysis process arises through suggesting the MDX queries or OLAP fragments according to the analyst preferences
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