An integrated ranking algorithm for efficient information computing in social networks

TL;DR

This paper proposes a new integrated ranking algorithm that leverages social network data and interlink analysis to improve web search results, addressing the dynamic and social nature of modern web content.

Contribution

The paper introduces a novel fused ranking model based on social forum interlinks and object inheritance graphs for more effective web object ranking.

Findings

Improved search result relevance demonstrated in experiments

Effective identification of relationships between web objects across social networks

Enhanced ranking accuracy over traditional methods

Abstract

Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.