Main Reference PaperKvasir: Scalable Provision of Semantically Relevant Web Content on Big Data Framework, IEEE Transactions on BigData, 2016[J2EE/Hadoop].
  • Kvasir achieves the scalability challenges in web browsing. when a user is browsing a web page, Kvasir is automatically display the similar web pages from high dimensional databases. The ranking of the search results are displayed based on the cosine similarity. To improve the indexing and querying efficiency, the parallel RP-Tree algorithm and stochastic SVD is implemented on Spark.

+ Description
  • Kvasir achieves the scalability challenges in web browsing. when a user is browsing a web page, Kvasir is automatically display the similar web pages from high dimensional databases. The ranking of the search results are displayed based on the cosine similarity. To improve the indexing and querying efficiency, the parallel RP-Tree algorithm and stochastic SVD is implemented on Spark.

  • To retrieve the similar articles from high dimensional databases.

  • To achieve the scalability.

  • To improve the search accuracy.

+ Aim & Objectives
  • To retrieve the similar articles from high dimensional databases.

  • To achieve the scalability.

  • To improve the search accuracy.

  • This work may contributes privacy in Kvasir, the personalized results provide based on the user’s browsing history.

+ Contribution
  • This work may contributes privacy in Kvasir, the personalized results provide based on the user’s browsing history.

  • Java JDK 1.8, Hadoop 1.2.1, MySQL 5.5.40.

  • Netbeans 8.0.1, J2EE, Hadoop, Apache Spark.

+ Software Tools & Technologies
  • Java JDK 1.8, Hadoop 1.2.1, MySQL 5.5.40.

  • Netbeans 8.0.1, J2EE, Hadoop, Apache Spark.

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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