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Decision lists

The basic idea of decision lists is to determine the strength of the link between a token and its trigger, and this is done by measuring the frequency of occurrence. In the following table (taken from [507]), we see the raw counts which have been found for the token bass  [Pg.86]

P(BASS-FISH guitar,bass) P(bass-music guitar,bass) We then compute the log-likelihood ratios for each collocation  [Pg.86]

At run time, we simply start at the top of the list and progress downwards imtil we find file collocation which matches our input sentence. We then take the word that results fi om that as the answer. There are many subtle modifications, which for instance smoolli file probability estimates, count all the evidence (not just the best case) and which consider the conditional probability of a word being the answer when we have several triggers present. Yarowsky notes however that the simple approach is often good enough that many of these modifications don t add any extra accuracy. [Pg.87]

From this it is clear that the trigger words are very strong disambiguation indicators, but also that some triggers occur more frequently that others. From these coimts, we can calculate tbe conditional probability of seeing a word given the collocation, e.g. [Pg.86]

We tben compute the log-likelihood ratios for each collocation  [Pg.86]


In sharp contrast, in trade secrets each state has its own law. Historically, this law is derived primarily from judicial interpretation of the English common law. Some states use the Code Napoleon or Spanish law as a background. As set forth in Stamicarbon N.V. vs. American Cyanamid Co. (3), no fewer than 20 states during the past nine years have enacted statues making appropriation or unauthorized disclosure of trade secrets a crime. The decision lists the states. One commendable statute is that in New Jersey (4). [Pg.43]

Figure 8.10 Decision list derived from mutagenicity data.l40] Arrows indicate the direction to follow if a substructure is (Y) or is not (N) present in a compound. The number of mutagens, the total number of compounds and the percentage of mutagens is indicated for each subset (right). Figure 8.10 Decision list derived from mutagenicity data.l40] Arrows indicate the direction to follow if a substructure is (Y) or is not (N) present in a compound. The number of mutagens, the total number of compounds and the percentage of mutagens is indicated for each subset (right).
Decisions. Upon the Minister of Public Health visa, decisions listed for proceedings are put into practice. A letter related to different decisions is addressed to the MA applicant. [Pg.740]

Yarowsky, D. 2000. Hierarchical decision lists for word sense disambiguation. Computers and the Humanities 34 179-86. [Pg.192]

Popular classifiers include context-sensitive rewrite rules, decision lists, decision trees, naive Bayes classifiers and HMM taggers. [Pg.110]

Rivest, R. L. Learning decision lists. Machine Learning 2 (1987), 229-246. [Pg.594]

A typical supply chain manager has to make the decisions listed below. Categorize each decision as strategic, tactical, or operational and briefly justify your choice. [Pg.23]

The decisions listed above do not provide an exhaustive list of all supply chain configuration decisions. That, especially, applies to policy decisions. Decisions relevant to a particular decision-making problem, and decision variables characterizing these decisimis, are defined during the supply chain configuration problemsolving process. [Pg.35]


See other pages where Decision lists is mentioned: [Pg.216]    [Pg.218]    [Pg.10]    [Pg.86]    [Pg.86]    [Pg.87]    [Pg.88]    [Pg.545]    [Pg.85]    [Pg.85]    [Pg.86]    [Pg.87]   


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