• REHAN KHAN
• A.J. SINGH

Information Extraction serves out to be the keen area of NLP by virtue of analyzing the essential data in the state space with varying fields of information that’s contained in a document. Being the major AI field for developing other fields of computer science and electronics like robotics for better human – machine interaction, IE tends to be a major key. For this major key the main domain for better evaluation and exploration with due efficiency and better response is the finite state space search and this search mechanism can be made more explosive by virtue of deploying the efficient algorithm that saves time, cost, with better precision and relative recall rate for essential data classification. This paper creates a novel approach for developing a better IE evaluation system based on the pre-established algorithms for the state space search in a fashion of a tunneling model with an agent to goal approach. MoveGen & GoalTest functions represent the respective states the agent is at present while OPEN & CLOSED functions represent the respective visited and not visited states of the space search.

State space search, information extraction, search algorithms, heuristics.

"NLP: A Comparative Study with Algorithmic Approach for Information Extraction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.970-979, September-2018, Available :http://www.jetir.org/papers/JETIR1809794.pdf

"NLP: A Comparative Study with Algorithmic Approach for Information Extraction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp970-979, September-2018, Available at : http://www.jetir.org/papers/JETIR1809794.pdf