Survey Algoritma Web-Snippet Clustering pada Search Engine

Abstract

Search engine menerapkan metode clustering untuk mempermudah pengguna mengakses output hasil query. Search engine dituntut menghasilkan output secara cepat dan akurat, sehingga algoritma clustering yang diterapkan harus mendukung hal tersebut. Paper ini membahas tiga buah algoritma web-snippet clustering dan perbandingan pencapaian ketiga algoritma tersebut terhadap kebutuhan khusus algoritma clustering pada search engine. Tiga algoritma tersebut adalah algoritma Snippet Aggregation for Knowledge Extraction (SNAKET), Suffix Tree Clustering (STC), dan Clustering berbasis Frequent Word Sequence (CFWS). Dari ketiga algoritma tersebut algoritma CFWS mempunyai performansi paling bagus karena mencapai enam dari tujuh kebutuhan khusus algoritma clustering pada search engine.

Kata Kunci: Search engine, clustering, web-snippet clustering

REFERENCE

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[3] Geraci, Filippo., Pellegrini, Marco., Pisati, Paolo., Sebastiani, Fabrizio., A Scalable Algorithm for High-Quality Clustering of Web Snippets, ACM SAC06, 2006.

[4] Li, Yanjun., Chung, Soon., Text Document Clustering Based on Frequent Word Sequences, ACM CIKM05, 2005

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[8] Zeng, Hua-Jun., He, Qi-Cai., Chen, Zeng., Ma, Wei-Ying, Ma, Jinwen., Learning to Cluster Web Search Results, Proceeding ACM Sigir04, 2004.

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