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Crossword puzzles are used everyday by millions of people for entertainment, but have applications also in educational and rehabilitation contexts. Unfortunately, the generation of ad-hoc puzzles, especially on specific subjects, typically requires a great deal of human expert work. This paper presents the architecture of WebCrow-generation, a system that is able to generate crosswords with no human intervention, including clue generation and crossword compilation. In particular, the proposed system crawls information sources on the Web, extracts definitions from the downloaded pages using state-of-the-art natural language processing techniques and, finally, compiles the crossword schema with the extracted definitions by constraint satisfaction programming. The system has been tested on the creation of Italian crosswords, but the extensive use of machine learning makes the system easily portable to other languages. [ABSTRACT FROM AUTHOR]