论文标题
Crictrs：基于嵌入的统计和半监督板球团队推荐系统
CRICTRS: Embeddings based Statistical and Semi Supervised Cricket Team Recommendation System
论文作者
论文摘要
团队推荐一直是团队运动的一个挑战性方面。这样的系统旨在推荐最适合反对派球员的球员组合，从而取得最佳结果。在本文中，我们提出了一种半监督的统计方法，通过将玩家建模为嵌入方式，以建立板球的团队推荐系统。为了构建这些嵌入，我们设计了一个定性和定量的评级系统，该系统也考虑了反对派的力量，以评估球员性能。获得的嵌入，根据玩家过去的表现来描述玩家的优势和劣势。我们还踏上了团队组成的关键方面，其中包括团队中击球手和保龄球的数量。团队组合会随着时间的推移而变化，具体取决于难以预测的不同因素，因此我们从用户那里获取此输入，并使用玩家嵌入来确定最佳的团队组合与给定的团队组成。
Team Recommendation has always been a challenging aspect in team sports. Such systems aim to recommend a player combination best suited against the opposition players, resulting in an optimal outcome. In this paper, we propose a semi-supervised statistical approach to build a team recommendation system for cricket by modelling players into embeddings. To build these embeddings, we design a qualitative and quantitative rating system which considers the strength of opposition also for evaluating player performance. The embeddings obtained, describes the strengths and weaknesses of the players based on past performances of the player. We also embark on a critical aspect of team composition, which includes the number of batsmen and bowlers in the team. The team composition changes over time, depending on different factors which are tough to predict, so we take this input from the user and use the player embeddings to decide the best possible team combination with the given team composition.
