
Abstract Standard alphabetical procedures for organizing lexical information put together words that are spelled alike and scatter words with similar or related meanings haphazardly through the list. Unfortunately, there is no obvious alternative, no other simple way for lexicographers to keep track of what has been done or for readers to find the word they are looking for. But a frequent objection to this solution is that finding things on an alphabetical list can be tedious and time-consuming. Many people who would like to refer to a dictionary decide not to bother with it because finding the information would interrupt their work and break their train of thought. In this age of computers, however, there is an answer to that complaint. One obvious reason to resort to on-line dictionaries – lexical databases that can be read by computers – is that computers can search such alphabetical lists much faster than people can. A dictionary entry can be available as soon as the target word is selected or typed into the keyboard. Moreover, since dictionaries are printed from tapes that are read by computers, it is a relatively simple matter to convert those tapes into the appropriate kind of lexical database. Putting conventional dictionaries on line seems a simple and natural marriage of the old and the new. Once computers are enlisted in the service of dictionary users, however, it quickly becomes apparent that it is grossly inefficient to use these powerful machines as little more than rapid page-turners. The challenge is to think what further use to make of them. WordNet is a proposal for a more effective combination of traditional lexicographic information and modern high-speed computation.
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3K | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.01% | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
