By Johan Bos (auth.), Bengt Nordström, Aarne Ranta (eds.)
This e-book constitutes the refereed lawsuits of the sixth overseas convention on typical Language Processing, GoTAL 2008, Gothenburg, Sweden, August 2008.
The forty four revised complete papers offered including three invited talks have been conscientiously reviewed and chosen from 107 submissions. The papers tackle all present concerns in computational linguistics and monolingual and multilingual clever language processing - concept, equipment and applications.
Read Online or Download Advances in Natural Language Processing: 6th International Conference, GoTAL 2008 Gothenburg, Sweden, August 25-27, 2008 Proceedings PDF
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Additional info for Advances in Natural Language Processing: 6th International Conference, GoTAL 2008 Gothenburg, Sweden, August 25-27, 2008 Proceedings
9 ] [issue7 , . . 9 ] [today8 , . . 9 ]    25 New Arc (2, det, 1) (7, det, 6) (5, pc, 7) (2, nmod, 5) (4, adv, 8) (3, vg, 4) (3, sbj, 2) (3, p, 9) (0, root, 3) Fig. 8. Transition sequence for parsing the English sentence in Figure 1 (σ[m] in bold) As before, the outer while loop is executed once for each word wi (1 ≤ i ≤ n), which is inserted at the head of the list σ. The ﬁrst inner while loop inserts wi in its proper place, by performing the required number of Swap transitions, and the second inner while loop adds the required number of arcs before the next word is shifted to σ.
N-gram gives better accuracy for both phases of the experiment. It is clear that bigrams and trigrams are able to capture the context in a better way as compared to unigrams. A drawback of including bigrams and trigrams is that they increase the complexity. Parts-of-Speech Tags: To distinguish between diﬀerent usages of same feature word, we added POS tags to unigrams. Unigram + POS lists the results for both the phases in Table 3 and Table 4. 1% for book data. So, part-ofspeech tags alone are not able to provide any additional beneﬁt for the task of sentiment analysis.
This dataset contains about 6,900 diﬀerent unigrams. Third dataset is a collection of book reviews collected from amazon website8 . We mined the book reviews to extract one-line comments given by users before the start of each descriptive review. Reviews with 4 or 5 star rating were considered as positive, while 1 and 2 star reviews were taken as negative. This dataset contains 4000 positive and 4000 negative sentences9 and consists of about 6,000 diﬀerent unigrams with average length of each sentence being close to 14 words.