Aspect-based Sentiment Evaluation of Chess Moves (ASSESS): an NLP-based Method for Evaluating Chess Strategies from Textbooks

TL;DR

This paper introduces ASSESS, an NLP-based aspect sentiment analysis method tailored for evaluating chess strategies from textbooks, enabling more nuanced understanding of move contexts and sentiments.

Contribution

It presents a novel application of aspect-based sentiment analysis to chess move evaluation, advancing NLP techniques in strategic game analysis from unstructured text.

Findings

The ABSA model effectively classifies sentiments related to chess moves.

Empirical results show improved accuracy over baseline methods.

The approach demonstrates practical applicability in analyzing chess textbooks.

Abstract

The chess domain is well-suited for creating an artificial intelligence (AI) system that mimics real-world challenges, including decision-making. Throughout the years, minimal attention has been paid to investigating insights derived from unstructured chess data sources. In this study, we examine the complicated relationships between multiple referenced moves in a chess-teaching textbook, and propose a novel method designed to encapsulate chess knowledge derived from move-action phrases. This study investigates the feasibility of using a modified sentiment analysis method as a means for evaluating chess moves based on text. Our proposed Aspect-Based Sentiment Analysis (ABSA) method represents an advancement in evaluating the sentiment associated with referenced chess moves. By extracting insights from move-action phrases, our approach aims to provide a more fine-grained and contextually aware `chess move'-based sentiment classification. Through empirical experiments and analysis, we evaluate the performance of our fine-tuned ABSA model, presenting results that confirm the efficiency of our approach in advancing aspect-based sentiment classification within the chess domain. This research contributes to the area of game-playing by machines and shows the practical applicability of leveraging NLP techniques to understand the context of strategic games.