APPROACH TO BIOMEDICAL TERM DISAMBIGUATION

(2006). We believe that our approach shows promiseand leads us to our goal of exploring the use ofbiomedical knowledge sources.In the future, we would also like to increase thesize of our conflated dataset and possibly create abiomedical all-words disambiguation test set <[r]

5.2 Weakly Supervised Learning While the previous section shows that we can benefit from substantially larger training corpora without needing significant additional manual annotation, it would be ideal if we could improve classification accuracy using only our seed annotated corpus and the large un[r]

Proceedings of EACL '99 Word Sense Disambiguation in Untagged Text based on Term Weight Learning Fumiyo Fukumoto and Yoshimi Suzukit Department of Computer Science and Media Engineering, Yamanashi University 4-3-11 Takeda, Kofu 400-8511 Japan {fukumoto@skye.esb, ysuzuki@windermere.alps[r]

data. This algorithm thus proceeds iteratively in-creasing the seed size in successive iterations. Thismonolingual bootstrapping method showed promisewhen tested on a limited set of target words but wasnot tried for all-words WSD.The failure of monolingual approaches (Ng andLee, 1996; Lee et al., 20[r]

improves with experience and study.Always be a student and keep learning.59. Beware of all tips and insideinformation. Wait for the market's actionto tell you if the information you'veobtained is accurate, then take a positionwith the developing trend.60. Buy the rumor, sell the news.61. K.I.S.S – K[r]

spoken and written styles. Based on this hypothesis, many terms repeat themselves with the same meaning in all their occurrences. Within the context of determining the sense of an abbreviation, it may be assumed that authors tend to use the same words in the vicinity of a specific long form o[r]

expansion of a long form adriamycin, which hasa higher score than effect of adriamycin. As wediscussed previously, the candidate effect of adri-amycin is skipped since it contains unnecessaryword(s) to form an acronym. Similarly, we prunethe candidate minimi because it forms a part of an-othe[r]

improves with experience and study.Always be a student and keep learning.59. Beware of all tips and insideinformation. Wait for the market's actionto tell you if the information you'veobtained is accurate, then take a positionwith the developing trend.60. Buy the rumor, sell the news.61. K.I.S.S – K[r]

We discuss this issue in our report with reference to performance reporting standards promulgated by the Destination Marketing Association International (DMAI). Acknowledging the difculty of nding direct cause-effect measures in an industry that traditionally relies on professional judgment[r]

interstitial fluid balance, and immune function. This is the first step for developing new drugs and therapies for enhancing or inhibiting lymphatic growth, and for treating various lymphatic disorders such as lymphedema and lymphoma. 9 CHAPTER II DEVELOPMENT OF A HIGH SPEED IMAGING SYSTEM* In view[r]

maximum of 21 days, baseline rSO2 for preterm infants (gestational age of 29-34 weeks) differed from established pediatric norms, while values for term neonates in the first days of life did not (McNeill et al., 2010, 2011). The observation by McNeill (McNeill et al., 2010, 2011) that cerebra[r]

Many systems that use NLP methods – such asdialogue systems, paraphrasing and summariza-tion, language generation, information extraction,machine translation, etc. – would benefit from be-ing able to recognize nonliteral language. Con-sider an example based on a similar example froman automate[r]

-score of 0.326.Although this is relatively low for a classificationtask, these results improve upon the baseline clas-sification scheme (all extracted terms are usefulfor indexing) with an F1-score of 0.182 (Demner-Fushman et al., 2008). Thus, non-lexical featurescan be leveraged, albeit to a[r]

and also associated with some facilities for search and use of services (Borgman, 1999), makes use of telecommunications and particularly the Internet to facilitate access to its contents remotely or locally through various connected systems that provide control and preservation of res[r]

also received great deal of attention for denoising of signalshaving multiresolution characteristics such as the electrocar-diogram [8–12].Besides the above algorithms, baseline wandering re-moval has been addressed in the literature individually. Base-line estimation using cubic spline [13], baseli[r]

algorithms are available for the pupil detection in an image frame and pupil centroid coor-dinates extraction, nevertheless environmental lighting conditions can affect the automaticdetection (Eizenman et al. 1984) (Landau 1987). Thus, IR light is used together with videorecording, so that the pupil[r]

huge opportunity cost for him to spend time with you. • Don’t look for instant results. As much as this is mentoring, this works like a long-term relationship building exercise and it takes time to get results. • Don’t look for answers. The mentor is not there to solve yo[r]

and depend on many other parameters. Finally, it is impor-tant to notice that this method can be applied to whateverkind of signals presenting changes in frequency or amplitude.Both methods (DCS and MDCS) were tested on simu-lated data made of 1000 segments of white noise with a vari-a[r]

extraction itself is performed using pattern matchingon the argument structure. The system extracts 23 %of the argument structures uniquely, and 24% withambiguity. Sasaki et al. (2008) present a supervisedmachine learning system that extracts event framesfrom a corpus in which the biological process[r]

strategic homeland security risks, the assessed consequences may include difficult-to-quantify psychological impacts in addition to consequences such as lives lost and economic damage. Structured techniques, such as value focused thinking, can help the analyst determine which aspects o[r]