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Patent Document Clustering Using Dimensionality Reduction

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 564))

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Abstract

Patents are a type of intellectual property rights that provide exclusive rights to the invention. Whenever there is a novelty or an invention, prior art search on patents is carried out to check the degree of innovation. Clustering is used to group the relevant documents of prior art search to gain insights about the patent document. The patent documents represent hundreds of features (words extracted from the title and abstract fields). The common sets of features between the documents are subtle. Therefore, the number of features for clustering increases drastically. This leads to the curse of dimensionality. Hence, in this work, dimensionality reduction techniques such as PCA and SVD are employed to compare and analyze the quality of clusters formed from the Google patent documents. This comparative analysis was performed by considering title, abstract, and classification code fields of the patent document. Classification code information was used to decide the number of clusters.

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Authors and Affiliations

  1. Department of Information Science and Technology, Anna University, Chennai, 600025, India

    K. Girthana & S. Swamynathan

Authors
  1. K. Girthana
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  2. S. Swamynathan
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Corresponding author

Correspondence to K. Girthana .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Białystok, Poland

    Khalid Saeed

  2. Dept. of Computer Science & Engg., University of Calcutta Dept. of Computer Science & Engg., Kolkata, West Bengal, India

    Nabendu Chaki

  3. C. V. Raman College of Engineering, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  4. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Sambit Bakshi

  5. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Girthana, K., Swamynathan, S. (2018). Patent Document Clustering Using Dimensionality Reduction. In: Saeed, K., Chaki, N., Pati, B., Bakshi, S., Mohapatra, D. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 564. Springer, Singapore. https://doi.org/10.1007/978-981-10-6875-1_17

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  • DOI: https://doi.org/10.1007/978-981-10-6875-1_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6874-4

  • Online ISBN: 978-981-10-6875-1

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