WebCrow

Key takeaways

WebCrow belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect WebCrow to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of WebCrow from memory before moving on to harder problems.

Reference excerpt

The WebCrow is a research project carried out at the Information Engineering Department of the University of Siena with the purpose of automatically solving crosswords.

The Project The scientific relevance of the project can be understood considering that cracking crosswords requires human-level knowledge. Unlike chess and related games and there is no closed world configuration space. A first nucleus of technology, such as search engines, information retrieval, and machine learning techniques enable computers to enfold with semantics real-life concepts. The project is based on a software system whose major assumption is to attack crosswords making use of the Web as its primary source of knowledge. WebCrow is very fast and often thrashes human challengers in competitions, especially on multi language crossword schemes. A distinct feature of the WebCrow software system is to combine properly natural language processing (NLP) techniques, the Google web search engine, and constraint satisfaction algorithms from artificial intelligence to acquire knowledge and to fill the schema. The most important component of WebCrow is the Web Search Module (WSM), which implements a domain specific web based question answering algorithm. The way WebCrow approaches crosswords solving is quite different with respect to humans: Whereas we tend to first answer clues we are sure of and then proceed filling the schema by exploiting the already answered clues as hints, WebCrow uses two clearly distinct stages. In the first one, it processes all the clues and tries to answer them all: For each clue it finds many possible candidates and sorts them according to complex ranking models mainly based on a probability criteria. In the second stage, WebCrow uses constraint satisfaction algorithms to fill the grid with the overall most likely combination of clue answers. In order to interact with Google, first of all, WebCrow needs to compose queries on the basis of the given clues. This is done by query expansion, whose purpose is to convert the clue into a query expressed by a simplified and more appropriate language for Google. The retrieved documents are parsed so as to extract a list of word candidates that are congruent with the crossword length constraints. Crosswords can hardly be faced by using encyclopedic knowledge only, since many clues are wordplays or are otherwise purposefully very ambiguous. This enigmatic component of crosswords is faced by a massive use of database of solved crosswords, and by automatic reasoning on a properly organized knowledge base of wired rules. Last but not the least, the final constraint satisfaction step is very effective to fill the correct candidate, even though, unlike humans, the system can not rely on very high confidence on the correctness of the answer.

Competitions WebCrow speed and effectiveness has been tested many times in man-machine competitions on Italian, English and multi-language crosswords The outcome of the tests is that WebCrow can successfully compete with average human players on single language schemes and reaches expert level performance in multi-language crosswords. However, WebCrow has not reached expert level in single-language crosswords, yet.

ECAI-06 Competition On August 30, 2006, at the European Conference on Artificial Intelligence (ECAI2006), 25 conference attendees and 53 internet connected crosswords lovers, competed with WebCrow in an official challenge organized within the conference program. The challenge consisted in 5 different crosswords (2 in Italian, 2 in English and one multi-language in Italian and English) and 15 minutes were assigned for each crossword. WebCrow ranked 21 out of 74 participants in the Italian competition, and won both the bilingual and English competitions.

Other Competitions Several competitions have been held in Florence, Italy within the Creativity Festival in December 2006, and another official conference competition took place in Hyderabad, India in January 2007, within the International Conference of Artificial Intelligence, where it ranked second out of 25 participants.

References

External links The WebCrow Website Google as AI I’m puzzled, Dr. Dobbs portal Crossword-solving system strikes a blow for AI, by Simon Aughton Crosswords at the crossroads with “il computer enigmista?”, Blogos - news and views on languages and technologies cbc.ca radio cruciverb.com Crossword Software Thrashes Human Challengers, The New Scientist

Worked examples

Example 1 — a first encounter with WebCrow

Start with the simplest possible case. Write down what WebCrow claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to WebCrow before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about WebCrow ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of WebCrow

In research: WebCrow appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses WebCrow in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: WebCrow is common in secondary-school and first-year university syllabi. It links to neighbouring topics Applications of artificial intelligence, so understanding it makes those chapters shorter.
In everyday life: Look for WebCrow outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

How to study WebCrow in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what WebCrow means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain WebCrow out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is WebCrow in simple terms?

The WebCrow is a research project carried out at the Information Engineering Department of the University of Siena with the purpose of automatically solving crosswords. The Project The scientific relevance of the project can be understood considering that cracking crosswords requires human-level kn…

Why does WebCrow matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study WebCrow?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on WebCrow.