Deciphering the Indus Valley Script: Hierarchical Clustering and Dependency Tree Analysis

This study introduces a pioneering methodology aimed at deciphering the enigmatic Indus script, leveraging advanced computational linguistic techniques in conjunction with the Interactive Corpus of Indus Texts (ICIT).The approach utilizes hierarchical clustering and dependency tree construction to organize symbols based on visual similarities and uncover grammatical structures within sequences of Indus script symbols.Through meticulous analysis, nuanced insights into the distribution, significance, and syntactic relationships of symbols are revealed.Notably, the investigation identifies patterns in frequently occurring combinations and their positional arrangements.Additionally, the study explores network properties of symbols, elucidating their centrality and contextual versatility within the script's semantic framework.Employing probabilistic models, the research investigates the predictive potential of positional patterns in reconstructing missing symbols, offering promising avenues for future decryption endeavors.Furthermore, multi-sequence alignment is utilized to identify underlying grammar patterns within the language.This innovative approach, coupled with substantive findings, contributes significantly to ongoing decipherment endeavors, shedding new light on one of humanity's oldest linguistic mysteries.