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Large Graphs Compression using a combined algorithm

Credit to Download: 1 | Page Numbers 6 | Abstract Views: 651
Year: 2014
COI code: DCEAEM01_155
Paper Language: English

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Authors Large Graphs Compression using a combined algorithm

Nafiseh Lavari Lashtaghani - International Center Asaloye PayamNoor Univ. of Iran
Saman Dehghanian - Islamic Azad Univ. of Dariun, Iran


Web Graph provides a framework for large-scale graph compression; it is the foundation of many real-world datasets. The increasing size of graphs presents a major obstacle in exploiting modern compression techniques. Recently some techniques have proved sufficiently efficient in allowing greater storage of Web graphs in a limited memory. These techniques mainly use repetitions that exist in the graphs for compressing purposes. In this paper I use similarity property technique based on the pages that are proximal in the lexicographic ordering which tend to have similar sets of neighbors. This technique together with an optimized Greedy algorithm can produce a new combinational algorithm that can be used to compress Web graph more efficiently


Web graph, compression, similarity, Greedy algorithm

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COI code: DCEAEM01_155

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Lavari Lashtaghani, Nafiseh & Saman Dehghanian, 2014, Large Graphs Compression using a combined algorithm, 1st National Conference on Development of Civil Engineering, Architecure,Electricity and Mechanical in Iran, گرگان, شركت مهندسي عمران بناي تدبير با همكاري دانشگاه گلستا, دانشگاه گلستان, the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
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