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word count facility

  • 1 word count facility

    fonction f de comptage de mots

    English-French business dictionary > word count facility

  • 2 word

    word [wɜ:d]
    mot ⇒ 1 (a)-(c) parole ⇒ 1 (a), 1 (b), 1 (d) nouvelles ⇒ 1 (c) message ⇒ 1 (c) promesse ⇒ 1 (d) conseil ⇒ 1 (e) bruit ⇒ 1 (f) ordre ⇒ 1 (g) rédiger ⇒ 2 (a)
    1 noun
    (a) (gen → written) mot m; (→ spoken) mot m, parole f;
    ∎ the words of a song les paroles d'une chanson;
    ∎ ironic (what) fine words! quelles belles paroles!;
    ∎ what is the Russian word for "head"?, what is the word for "head" in Russian? comment dit-on "head" en russe?;
    ∎ the Japanese don't have a word for it les Japonais n'ont pas de mot pour dire cela;
    ∎ she can't put her ideas/her feelings into words elle ne trouve pas les mots pour exprimer ses idées/ce qu'elle ressent;
    ∎ I can't find (the) words to tell you how glad I am! je ne saurais vous dire à quel point je suis content!;
    ∎ there are no words to describe or words cannot describe how I feel aucun mot ne peut décrire ce que je ressens;
    ∎ they left without (saying) a word ils sont partis sans (dire) un mot;
    ∎ with these words they left sur ces mots ou là-dessus, ils sont partis;
    ∎ lazy isn't the word for it! paresseux, c'est peu dire!;
    ∎ idle would be a better word oisif serait plus juste;
    ∎ figurative he doesn't know the meaning of the word "generosity" il ne sait pas ce que veut dire le mot "générosité";
    ∎ he's mad, there's no other word for it il est fou, il n'y a pas d'autre mot;
    ∎ there's a word for people like you, it's "thief" les gens dans ton genre, on les appelle des voleurs;
    ∎ I didn't understand a word of the lecture je n'ai pas compris un mot de la conférence;
    ∎ he doesn't know a word of German il ne sait pas un mot d'allemand;
    ∎ I don't believe a word of it! je n'en crois pas un mot!;
    ∎ that's my last or my final word on the matter c'est mon dernier mot (sur la question);
    ∎ those were his dying words ce sont les dernières paroles qu'il a prononcées avant de mourir;
    ∎ she said a few words of welcome elle a dit quelques mots de bienvenue;
    ∎ I gave him a few words of advice je lui ai donné quelques conseils;
    ∎ I gave him a few words of encouragement je lui ai dit quelques mots d'encouragement;
    ∎ can I give you a word of warning/of advice? puis-je vous mettre en garde/vous conseiller?;
    ∎ he didn't say a word il n'a rien dit, il n'a pas dit un mot;
    ∎ I can't get a word out of her je ne peux pas en tirer un mot;
    ∎ and now a word from our sponsors et maintenant, voici un message publicitaire de nos sponsors;
    ∎ I'm a woman of few words je ne suis pas quelqu'un qui fait de grands discours;
    ∎ he's a man of few words c'est un homme peu loquace, c'est quelqu'un qui n'aime pas beaucoup parler;
    ∎ in the words of Shelley comme l'a dit Shelley;
    ∎ in the words of his boss, he's a layabout à en croire son patron ou d'après (ce que dit) son patron, c'est un fainéant;
    ∎ tell me in your own words dites-le moi à votre façon ou avec vos propres mots;
    ∎ he told me in so many words that I was a liar il m'a dit carrément ou sans mâcher ses mots que j'étais un menteur;
    ∎ she didn't say it in so many words but her meaning was quite clear elle n'a pas dit exactement cela, mais c'était sous-entendu;
    ∎ a six-hundred-word article un article de six cents mots;
    ∎ by or through word of mouth oralement;
    ∎ the news spread by word of mouth la nouvelle se répandit de bouche à oreille;
    ∎ too beautiful for words d'une beauté extraordinaire;
    ∎ too stupid for words vraiment trop bête;
    ∎ word for word (translate) littéralement, mot à mot; (repeat) mot pour mot;
    ∎ from the word go dès le départ;
    ∎ (upon) my word! ma parole!, oh la la!;
    ∎ not a word! pas un mot!, bouche cousue!;
    ∎ don't put words into my mouth ne me faites pas dire ce que je n'ai pas dit;
    ∎ he took the words out of my mouth il a dit exactement ce que j'allais dire;
    ∎ words fail me! j'en perds la parole!, je suis stupéfait!;
    ∎ he never has a good word to say about anyone personne ne trouve jamais grâce à ses yeux;
    ∎ to put in a (good) word for sb glisser un mot en faveur de qn;
    ∎ to have the last word avoir le dernier mot;
    ∎ British it's the last word in comfort c'est ce qui se fait de mieux en matière de confort;
    ∎ British it's the last word in luxury c'est ce qu'on fait de plus luxueux
    (b) (talk) mot(s) m(pl), parole(s) f(pl);
    ∎ to have a word with sb about sth toucher un mot ou deux mots à qn au sujet de qch;
    ∎ can I have a word with you about the meeting? est-ce que je peux vous dire deux mots à propos de la réunion?;
    ∎ can I have a word? je voudrais vous parler un instant
    (c) (UNCOUNT) (news) nouvelle(s) f(pl); (message) message m, mot m;
    ∎ the word got out that there had been a coup la nouvelle d'un coup d'État a circulé;
    ∎ word came from Tokyo that the strike was over la nouvelle arriva de Tokyo que la grève était terminée;
    ∎ she brought them word of Tom elle leur a apporté des nouvelles de Tom;
    ∎ have you had any word from him? avez-vous eu de ses nouvelles?;
    ∎ we have had no word from him nous sommes sans nouvelles de lui;
    ∎ she left word for us to follow elle nous a laissé un message pour dire que nous devions la suivre;
    ∎ to spread the word (proselytize) annoncer la bonne parole;
    ∎ spread the word that Mick's back in town faites passer la nouvelle ou faites dire que Mick est de retour en ville;
    ∎ he sent word to say he had arrived safely il a envoyé un mot pour dire qu'il était bien arrivé
    (d) (promise) parole f, promesse f;
    ∎ he gave his word that we wouldn't be harmed il a donné sa parole qu'il ne nous ferait aucun mal;
    ∎ I give you my word on it je vous en donne ma parole;
    ∎ she gave her solemn word elle a juré ou elle a promis solennellement;
    ∎ to break one's word manquer à sa parole;
    ∎ to go back on one's word revenir sur sa parole;
    ∎ we held or we kept her to her word nous l'avons obligée à tenir sa parole;
    ∎ to keep one's word tenir parole, tenir (sa) promesse;
    ∎ he was as good as his word il a tenu parole;
    ∎ she's a woman of her word c'est une femme de parole;
    ∎ I'm a man of my word je suis un homme de parole;
    ∎ word of honour! parole d'honneur!;
    ∎ we only have his word for it il n'y a que lui qui le dit, personne ne peut prouver le contraire;
    ∎ you can take my word for it vous pouvez me croire sur parole;
    ∎ we'll have to take your word for it nous sommes bien obligés de vous croire;
    ∎ take my word (for it), it's a bargain! croyez-moi, c'est une affaire!;
    ∎ I took her at her word je l'ai prise au mot;
    ∎ it's your word against mine c'est votre parole contre la mienne;
    ∎ my word is my bond je n'ai qu'une parole, je tiens toujours parole
    (e) (advice) conseil m;
    ∎ a word to travellers, watch your luggage! un petit conseil aux voyageurs, surveillez vos bagages!;
    ∎ a quick word in your ear je vous glisse un mot à l'oreille;
    ∎ a word to the wise à bon entendeur, salut
    (f) (rumour) bruit m;
    ∎ (the) word went round that he was dying le bruit a couru qu'il était sur le point de mourir
    (g) (order) ordre m;
    ∎ he gave the word to march il a donné l'ordre ou le signal de se mettre en marche;
    ∎ his word is law c'est lui qui fait la loi;
    ∎ just give or say the word and we'll be off vous n'avez qu'à donner le signal et nous partons
    (h) (watchword) mot m d'ordre; (password) mot m de passe;
    ∎ the word now is "democracy" le mot d'ordre maintenant, c'est "démocratie"
    (a) (letter, document) rédiger, formuler; (contract) rédiger;
    ∎ they worded the petition carefully ils ont choisi les termes de la pétition avec le plus grand soin;
    ∎ we sent a strongly worded protest nous avons envoyé une lettre de protestation bien sentie
    (b) Australian familiar (advise) conseiller□ ; (inform) informer□
    ∎ word (up)! (I agree) parfaitement!□ ; (it's true) sans dec!
    ∎ Religion the Word le Verbe;
    ∎ the Word of God la parole de Dieu
    British familiar (argument) dispute□ f;
    ∎ to have words se disputer□, avoir des mots;
    ∎ they had words about her drinking ils se sont disputés sur le fait qu'elle boit□
    en un mot
    autrement dit, en d'autres termes
    ►► word association association f d'idées par les mots;
    Linguistics word class classe f de mots;
    Computing word count nombre m des mots;
    ∎ to do a word count compter les mots;
    word count facility fonction f de comptage de mots;
    word game = jeu de lettres;
    word group groupe m de mots, membre m de phrase;
    word order ordre m des mots;
    word picture description f imagée ou pittoresque; (of person) portrait m en prose;
    word processing traitement m de texte;
    word processor logiciel m de traitement de texte;
    Typography word split coupure f de mot;
    Computing word wrap retour m à la ligne automatique

    Un panorama unique de l'anglais et du français > word

  • 3 word

    COMPUTING word count nombre m de mots;
    ∎ to do a word count compter les mots;
    word count facility fonction f de comptage de mots;
    word processing traitement m de texte;
    word processor machine f de traitement de texte

    English-French business dictionary > word

  • 4 Artificial Intelligence

       In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)
       Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)
       Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....
       When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)
       4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually
       Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)
       Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)
       What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)
       [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)
       The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)
       9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form
       The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)
       There are many different kinds of reasoning one might imagine:
        Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."
        Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)
       Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)
       Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)
       The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)
        14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation
       It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)
       We might distinguish among four kinds of AI.
       Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.
       Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.
    ... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)
       Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)
        16) Determination of Relevance of Rules in Particular Contexts
       Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)
       Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)
        18) The Assumption That the Mind Is a Formal System
       Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)
        19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence
       The primary goal of Artificial Intelligence is to make machines smarter.
       The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)
       The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....
       AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)
        21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions
       In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)
       Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)
       Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)
       The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

    Historical dictionary of quotations in cognitive science > Artificial Intelligence

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