... what to avoid:ߜ The spam approach. Avoid companies that contact you in a spammyway. Nearly everyone owning a domain has received a truckload ofe-mail from companies claiming that they’ve already ... storiesYahoo!, eBay, Amazon, and Google, whose domain names (and companynames) have little contextual meaning. If you own technology or a business model as groundbreaking and earth-shaking as each ... terrific program, but it’s a separate marketing campaign than basic site optimization. Certainonline marketing companies specialize in consulting or operatingAdWords campaigns, and they are discussed...
... Solutions may include: Replicate the database on the local client computer using MSDE, and then upload the new information to the main SQL Server database daily. Create a separate database and table ... timesheets are queried by last name to run several reports and queries. This situation has been identified as a performance problem by the database administrators, and they are requesting a fix as ... that only accept timesheet data. Replicate this data to the main database as needed. 5. Management must be able to run reports even if the rest of the system is unavailable. Solutions can...
... static variations for a single dynamically-generated page. If you are generating pages dynamically to provide frequently updated data, consider redesigning your application so that it generates ... high. A value from 0 through 20 is preferred. A value greater than 80 indicates insufficient random access memory (RAM). Memory: Available Bytes The amount of physical memory available to ... (HTML) pages, or Web applications, have much higher overhead than static HTML pages, their performance has a significant impact on Web server capacity. By monitoring applications and estimating...
... models that are discrimi-native, that are trained on as large a dataset as pos-sible, and that have a very large number of param-eters but are regularized (Halevy et al., 2009).When evaluating ... above.3 Conditionalrandom fields A linear-chain conditionalrandomfield (Laffertyet al., 2001) is a way to use a log-linear model for the sequence prediction task. We use the barnotation for ... the dataset us-ing PATGEN, and then hyphenate the remaining10% of the dataset using Liang’s algorithm and thelearned pattern file.The PATGEN tool has many user-settable pa-rameters. As is...
... Smith and J. Eisner. 2005. Contrastive estimation:Training log-linear models on unlabeled data. In ACL.Martin Szummer and Tommi Jaakkola. 2002. Partiallylabeled classification with markov random ... andT. Darrell. 2007. Hidden-state conditional random fields. In PAMI.H. Raghavan, O. Madani, and R. Jones. 2006. Activelearning with feedback on both features and instances.JMLR.R. Salakhutdinov, ... accuracy withthe addition of lower cost unlabeled data. Tradi-tional approaches to semi-supervised learning areapplied to cases in which there is a small amount offully labeled data and a...
... com-pression tasks achieved a significant com-pression rate without any loss.1 IntroductionThere has been an increase in available N -gramdata and a large amount of web-scaled N-gramdata has been ... Communication Science Laboratories2-4 Hikaridai Seika-cho Soraku-gun Kyoto 619-0237 Japan{taro,tsukada,isozaki}@cslab.kecl.ntt.co.jpAbstractEfficient processing of tera-scale text datais an important ... the ACL-IJCNLP 2009 Conference Short Papers, pages 341–344,Suntec, Singapore, 4 August 2009.c2009 ACL and AFNLP A Succinct N-gram Language Model Taro Watanabe Hajime Tsukada Hideki IsozakiNTT...
... value and the Model 1translation probability as real-valued features foreach candidate pair, as well as a normalised score67criminative model on a corpus of ten thousandword aligned Arabic-English ... Statistical phrase-based translation. In Proceedings of HLT-NAACL, pages81–88, Edmonton, Alberta.J. Lafferty, A. McCallum, and F. Pereira. 2001. Conditional random fields: Probabilistic models for ... is a strong alignment candidate. The sum of thesescores is also used as a feature. Each source wordand POS tag pair are used as indicator featureswhich allow the model to learn particular...
... a feature. All thefeature functions are real-valued and can use adja-cent label information.Semi-CRFs are actually a restricted version oforder-L CRFs in which all the labels in a chunk arethe ... applysemi-CRFs to Named Entity Recognitiontasks with a tractable computational cost.Our framework can handle an NER taskthat has long named entities and manylabels which increase the computationalcost. ... 2006.c2006 Association for Computational LinguisticsImproving the Scalability of Semi-Markov Conditional Random Fields for Named Entity RecognitionDaisuke Okanohara† Yusuke Miyao† Yoshimasa Tsuruoka...
... translation, we develop a discriminative or-der model. An advantage of such amodel is that wecan easily combine different kinds of features (suchas syntax-based and surface-based), and that ... Distortion models forstatistical machine translation. In ACL.D. Chiang. 2005. A hierarchical phrase-based model for statis-tical machine translation. In ACL.M. Collins. 2000. Discriminative reranking ... inference and train-ing of context-rich syntactic translation models. In ACL.P. Koehn. 2004. Pharaoh: A beam search decoder for phrase-based statistical machine translation models. In AMTA.R....
... Dis-criminative log-linear grammars with latent variables.In NIPS.Adwait Ratnaparkhi. 1997. A linear observed time sta-tistical parser based on maximum entropy models. InEMNLP 2, pages 1–10.Andreas ... indiscriminative parsing. In ACL 44, pages 873–880.Joseph Turian, Ben Wellington, and I. Dan Melamed.2007. Scalable discriminative learning for natural lan-guage parsing and translation. In Advances ... Petrov, Leon Barrett, Romain Thibaux, and DanKlein. 2006. Learning accurate, compact, and in-terpretable tree annotation. In ACL 44/COLING 21,pages 433–440.Slav Petrov, Adam Pauls, and Dan Klein....
... is part of the Lancaster Treebank corpusand contains 1473 sentences. Each sentence con-tains hand-labeled syntactic roles for natural lan-guage text. A. 200 A. 400 A. 600 A. 800 A. 1000 A. 1200 A. 14000.860.880.900.920.94B.200B.400B.600B.800B.1000B.1200B.14000.860.880.900.920.940.860.880.900.920.94FC.200C.400C.600C.800C.1000C.1200C.14000.860.880.900.920.940.860.880.900.920.94FFigure ... different model on the Lan-caster Treebank data set. The models used in thisevaluation were trained with observation data fromthe Lancaster Treebank training set. The trainingset and testing set are ... modified hiddenMarkov model Lin-Yi ChouUniversity of WaikatoHamiltonNew Zealandlc55@cs.waikato.ac.nzAbstractThis paper explores techniques to take ad-vantage of the fundamental difference...
... nominalattributes can have one of a (user-defined) closed setof possible values. The data model also supportsassociative relations between markables: Markableset relations associate arbitrarily many markableswith ... with a capital letter.Markables are the carriers of the actual annota-tion information. They can be queried by meansof string matching and by means of attribute-valuecombinations. A markable ... in a separate file. If these principles areobserved, annotation data management (incl. leveladdition, removal and replacement, but also conver-sion into and from other formats) is greatly facili-tated.The...
... (6)Rather than using mutual information as a measureof collocational strength, we used unigram, bigramand joint probabilities. Amodel that includes bothjoint probability and the unigram probabilities ... Computational Linguistics.J. Lafferty, A. McCallum, and F. Pereira. 2001. Conditional random fields: Probabilistic modelsfor segmenting and labeling sequence data. InProc. of 18th International ... phonologicalvariables, which capture aspects of rhythm and tim-ing that affect accentuation.4.1 Syntactic variablesThe only syntactic category we used was a four-way classification for hand-generated part of speech(POS):...