tailieunhanh - Báo cáo khoa học: "Predicting Clicks in a Vocabulary Learning System"

We consider the problem of predicting which words a student will click in a vocabulary learning system. Often a language learner will find value in the ability to look up the meaning of an unknown word while reading an electronic document by clicking the word. Highlighting words likely to be unknown to a reader is attractive due to drawing his or her attention to it and indicating that information is available. However, this option is usually done manually in vocabulary systems and online encyclopedias such as Wikipedia. Furthurmore, it is never on a per-user basis. . | Predicting Clicks in a Vocabulary Learning System Aaron Michelony Baskin School of Engineering University of California Santa Cruz 1156 High Street Santa Cruz CA 95060 amichelo@ Abstract We consider the problem of predicting which words a student will click in a vocabulary learning system. Often a language learner will find value in the ability to look up the meaning of an unknown word while reading an electronic document by clicking the word. Highlighting words likely to be unknown to a reader is attractive due to drawing his or her attention to it and indicating that information is available. However this option is usually done manually in vocabulary systems and online encyclopedias such as Wikipedia. Furthur-more it is never on a per-user basis. This paper presents an automated way of highlighting words likely to be unknown to the specific user. We present related work in search engine ranking a description of the study used to collect click data the experiment we performed using the random forest machine learning algorithm and finish with a discussion of future work. 1 Introduction When reading an article one occasionally encounters an unknown word for which one would like the definition. For students learning or mastering a language this can occur frequently. Using a computerized learning system it is possible to highlight words with which one would expect students to struggle. The highlighting both draws attention to the word and indicates that information about it is available. There are many applications of automatically highlighting unknown words. The first is obviously 99 educational applications. Another application is foreign language acquisition. Traditionally learners of foreign languages have had to look up unknown words in a dictionary. For reading on the computer unknown words are generally entered into an online dictionary which can be time-consuming. The automated highlighting of words could also be applied in an online encyclopedia .

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