Understanding Short Texts

Abstract

• Researchers in natural language processing, data management, knowledge engineering, text mining, and information retrieval; • Industrial practitioners in search, ads, seman-tic query processing, and other knowledge-powered applications. • Junior researchers and graduate students in text analysis, who are potentially interested in large-scale knowledge representation and acquisition, machine learning, graph algo-rithms. 2 Introduction Everyday, billions of short texts are being pro-duced, including search queries, ad keywords, tags, tweets, conversations in messengers, social network posts, etc. Unlike documents, short texts have some unique characteristics which make them difficult to handle. • First, short texts, especially search queries, do not always observe the syntax of a written language. This means traditional NLP tech-niques, such as syntactic parsing, do not al-ways apply to short texts with good results. • Second, short texts contain limited context. The majority of search queries contain less than 5 words, and tweets can have no more than 140 characters.