International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
Creation of Software focusing on Patent Analysis Kandare Dipak Prabhu, Bhosale Sayali Ravindra, Dhande Priyanka Umesh, Shaikh Nida Zahid Kandare Dipak Prabhu BE Student, PUNE UNIVERSITY, GESCOE, Nashik, Maharashtra, India. Bhosale Sayali Ravindra BE Student, PUNE UNIVERSITY, GESCOE , Nashik, Maharashtra, India. Dhande Priyanka Umesh BE Student, PUNE UNIVERSITY, GESCOE, Nashik, Maharashtra, India. Shaikh Nida Zahid BE Student, PUNE UNIVERSITY, GESCOE, Nashik, Maharashtra, India. Prof. C.B.Patil Internal guide GESCOE, Nashik, Maharashtra India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Within the early phases of technology
7. Interpretation: predict technology or business trends and relations[4].
management processes, patents are often used as a source of inspiration for new ideas. Patents contain detailed technical information about a technical problem and the preferred technical solution. This information can be used for example to assess the state of the art or as a basis to identify possible gaps in a technology field. But often it is a very time consuming process to analyse the information provided by patents, because huge amounts of patents have to be considered. Therefore special text-mining and data mining concept are used to help extracting the desired information in short time. Classification is used to classify the problem and its solution. Our approach to make an effective Pre-Processing steps to save both space and time requirements by using improved Stemming Algorithm. Stemming algorithms are used to transform the words in texts into their grammatical root form.
2. PROBLEM STATEMENT To analyse and register patent through software by using stemming and classification algorithm which were earlier register after checking problem statement and solution manually.
2.1 A GENERAL METHODOLOGY Patent analyses based on structured information such as filing dates, assignees, or citations have been the major approaches. These structured data can be analysed by bibliometric methods, data mining techniques, or well-established database management tools such as OLAP (On-Line Analytical Processing) modules[1].
Key Words: Extraction, Stemming, StopWordRemoval.
1.INTRODUCTION
Therefore, based on the patent analysis scenario introduced above, a text mining methodology specialized for full-text patent analysis is proposed. This may involve a repeated process of devising a set of query terms (query formulation), searching a couple of patent databases (collection selection), filtering undesired patents (relevance judgment), and downloading patents for local analysis (data crawling). Depending on the analysis purpose, the step can be as easy as, for example, fetching all the patents under some IPC (International Patent Classification) categories[2] .
Patent documents contain important research results that are valuable to the industry, business, law, and policy-making communities. If carefully analysed, they can show technological details and relations, reveal business trends, inspire novel industrial solutions, or help make investment policy (Campbell, 1983; Jung, 2003)[2]. In recent years, patent analysis had been recognized as an important task at the government level in some Asian countries.
1.1 A typical patent analysis scenario
The general text mining methodology for patent analysis. o Document Pre-processing - Collection Creation - Document Parsing and Segmentation - Text Summarization - Document Surrogate Selection o Indexing - Keyword/Phrase Extraction - Morphological Analysis - Stopword Filtering - Term Association and Clustering o Topic Clustering
1. Task identification: define the scope, concepts, and purposes for the analysis task 2. Searching: iteratively search, filter, and download related patents 3. Segmentation: segment, clean, and normalize structured and unstructured parts 4. Abstracting: analyse the patent content to summarize their claims, topics, functions, or technologies 5. Clustering: group or classify analysed patents based on some extracted attributes 6. Visualization: create technology-effect matrices or topic maps
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