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Insights on the hierarchy of letters in scrabble using cosine similarity, minimum spanning tree, and centrality analysis.
- Source :
-
AIP Conference Proceedings . 2024, Vol. 2895 Issue 1, p1-10. 10p. - Publication Year :
- 2024
-
Abstract
- This study aims to generate insights on the hierarchy and importance of letters in the game Scrabble by employing two operational research frameworks. Both frameworks begin by using a vector space model whose basis vectors are all the valid Scrabble words and where each letter is treated as a vector. A network of the letters is then constructed where the edge weight between each pair of letters is determined using the corresponding vectors' cosine similarity, which is effectively a measure of the co-occurrence rate of the two letters. The first framework continues by obtaining the minimum spanning tree of the network and performing centrality analysis on the MST. Through the first framework, a hierarchy of the letters is obtained. This hierarchical arrangement shows how letters lower in the hierarchy depend on higher-level letters. On the other hand, the second framework involves performing centrality analysis on the original network of letters and results in a ranking of letters based on their co-occurrence rate with other letters. Based on the frameworks in the study, letter E emerges as the highest ranked letter while the letter Q consistently ranks at the bottom. Thus, the study demonstrates how the two frameworks can be used for a novel application and other possible applications of a similar nature. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SPANNING trees
*COSINE function
*VECTOR spaces
*OPERATIONS research
Subjects
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 2895
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- AIP Conference Proceedings
- Publication Type :
- Conference
- Accession number :
- 175915268
- Full Text :
- https://doi.org/10.1063/5.0192067