نتایج جستجو برای: frequent items
تعداد نتایج: 199904 فیلتر نتایج به سال:
the hypothesis is that recent and frequent exposure to lexical items leads to a more fluent production of speech in terms of rate of speech. to test the hypothesis,a one-way anova experimental design was carried out. 24 sednior students of efl participated in a one-way interview test. data analyses revealed that those who were exposed frequently to the lexical items over a week prior to inter...
the hypothesis is that recent and frequent exposure to lexical items leads to a more fluent production of speech in terms of rate of speech. to test the hypothesis , a one- way anova experimental design was carried out. 24 senior student of efl participated in a one-way interview test. data analyses revealed that those who were exposed frequently to the lexical items over a week prior to inte...
داده کاوی پیش گویانه یک ابزار ضروری برای محققان و پزشکان بالینی تلقی می شود. درک مسائل مهم نهفته در این متدها و برنامه های کاربردی که مورد توافق قرار گرفته و استاندارد شده اند برای گسترش روند آن ها اجباری و منتشرکننده نتایج حاصل است. امروزه پزشکان با بهره گیری از فناوری های نوین اطلاعاتی می توانند از داده کاوی پیش گویانه بهره گرفته و در مسائل روزانه خود با هدف تسریع و کاهش هزینه های خدمات درمان...
this study investigates the effect of teacher’s repetition as an input enhancement technique in explicit teaching of vocabulary items on efl learners’ later retrieval. to this end, 66 persian speaking english learners, aged 18 - 29, homogenized through a standard proficiency test (opt), were chosen and put into two experimental and control groups, each 33 learners. general service list (gsl), a...
We present a deterministic parallel algorithm for the k–majority problem, that can be used to find in parallel frequent items, i.e., those whose multiplicity is greater than a given threshold, and is therefore useful in the context of iceberg queries and many other different contexts. The algorithm can be used both in the on–line (stream) context and in the off–line setting, the difference bein...
Monitoring frequently occuring items is a recurring task in a variety of applications. Although a number of solutions have been proposed there has been few to address the problem in a distributed networked environment. Most past solutions relied upon approximating results to lower communication overhead. In this paper we introduce a new algorithm designed for continuously tracking frequent item...
This paper presents new techniques for focusing the discovery of frequent itemsets within large, dense datasets containing highly frequent items. The existence of highly frequent items adds signi cantly to the cost of computing the complete set of frequent itemsets. Our approach allows for the exclusion of such items during the candidate generation phase of the Apriori algorithm. Afterwards, th...
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