Top-k字符串自动完成与同义词
Top-k String Auto-Completion with Synonyms
摘要：
自动补全是现代信息系统最显著的特征之一。现有的自动补全解决方案基于当前输入的字符序列的开始（即前缀）提供建议。然而，在许多实际应用中，一个实体往往有同义词或缩写。例如，“DBMS”是“数据库管理系统”的缩写。在本文中，我们研究了一种新的自动完成类型，使用同义词和缩略语。我们提出了三个基于trie树的算法来解决top-k自动补全与同义词，每一个具有不同的空间和时间复杂度权衡。大规模数据集上的实验表明，它是可能的，以支持有效和高效的基于同义词的检索百万字符串的完成与数千个同义词规则在大约一微秒每完成，而采取小的空间开销（即160-200字节每字符串）。我们实验的源代码可以在以下网址下载：http://udbms.cs.helsinki.fi/? projects/autocomplement/download .
英文摘要：
Auto-completion is one of the most prominent features of modern information systems. The existing solutions of auto-completion provide the suggestions based on the beginning of the currently input character sequence (i.e. prefix). However, in many real applications, one entity often has synonyms or abbreviations. For example, "DBMS" is an abbreviation of "Database Management Systems". In this paper, we study a novel type of auto-completion by using synonyms and abbreviations. We propose three trie-based algorithms to solve the top-k auto-completion with synonyms; each one with different space and time complexity trade-offs. Experiments on large-scale datasets show that it is possible to support effective and efficient synonym-based retrieval of completions of a million strings with thousands of synonyms rules at about a microsecond per-completion, while taking small space overhead (i.e. 160-200 bytes per string). The source code of our experiments can be download at: http://udbms.cs.helsinki.fi/?projects/autocompletion/download .
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
