AUTOMATED RESEARCH TOPIC SUGGESTION BASED ON PATENT CITATION ANALYSIS WITH COST AND SUCCESS ESTIMATION

Allocating new research work to researchers can be a challenging task. Whether it is for students of an academic institute or for researchers in a research lab/institute, the basic problems/ questions faced by the allocating body are the same, such as:
1) How to easily identify the topic for research?
2) How to estimate costs and timelines involved beforehand?
3) How to ensure success?
4) How to comprehensively identify competing technologies and parallel development.

This paper presents a tool for answering such questions of the allocating body, as well as automating the process of research topic selection alongwith cost and success estimation.

Briefly, this tool is based on citation analysis of a technology area, of the researcher, to whom the research topic needs to be allocated, and analysis of patent data for other estimations.

These other estimations include:
1) Selection of model inventions
2) Estimation of skillset required, and suggestion of co-inventor/s from group of researchers in the institute/company
3) Estimation of experimentation and material costs
4) Estimation of completion date
5) Success (technological and economical) estimation.

Accuracy of the tool and loopholes are discussed in the later part of the paper, alongwith solutions for minimising disadvantages of each loophole, and future scope of development for the tool.