... by first using the flat learning strat-egy to learn the discriminative functions for indi-vidual classes and then iteratively combining the two most relatedclasses using the cosine similar-ity ... from the given training set repeatedly. Then, each training sample set is used to train a certain discrimina-tive function. Finally, the final weight vector in the discriminative function is ... vector initialized as the zero vector. 2) Train the weight vector of the linear discriminative function for the “AT” relation type vs. all the remaining relation types (including the “NON” relation) ...
... respectively. Finally, we present experimental setting and results in Section 5 and conclude with some general observations in relation extractionin Section 6. 2 Related Work The relationextraction ... words of the mentions in the training data according to their indicating relationships. Two features are defined to include this information: • ET1SC2: combination of the entity type of M1 ... built by using the phrase head information returned by the Collins’ parser and linking all the other 5 http://ilk.kub.nl/~sabine/chunklink/ fragments in a phrase to its head. It also includes...
... re-lation extraction by mining wikipedia texts using in- formation from the web. In Proceedings of the JointConference of the 47th Annual Meeting of the ACLand the 4th International Joint Conference ... training example for each relation. In PROP,we used training articles for pattern prediction.87.3.2 Held-out Evaluation In the held-out evaluation, relation instances dis-covered from testing ... 20 times in the corpus.7.2.1 EvaluationWe split the data into training data and test data.The training data was Xrs for 12 relations and thetest data was that for the remaining 12 relations....
... engine is apart of the car so that the positive sentiment beingexpressed about the engine can also be attributed tothe car. In this paper we examine our preliminary resultsfrom applying a relation ... Proceedings of the 23rdInternational Conference on Computational Linguis-tics (Coling 2010).R E. Fan, K W. Chang, C J. Hsieh, X R. Wang, andC J. Lin. LIBLINEAR: A library for large linearclassification. ... Auto-motive Domain International AAAI Conference onWeblogs and Social Media Data Challenge Workshop.2010.Klein D. and Manning C. Accurate Unlexicalized Pars-ing. Proceedings of the 41st Meeting of...
... followed their owndefinitions of different scoring values, such as excludingcertain scores (see examples in table 1). They find the def-initions incorrect. If the veterinarian strictly follows ... effect inrelation to production parametersControl of clinical effectHerd statusFarmer's influenceInfluence of strategy in veterinary practiceIdeologyLegislationActa Veterinaria Scandinavica ... treatment of each individualcow, indicating that decisions can differ both within andbetween herds.At the farm level, the veterinarians seemed to integratefarm -related information into the decision...
... code. One thing you'll notice about ModifyingRelatedData.cs is that it calls PushChangesToDatabase() immediately after performing the following steps in the Main() method: 1. Adding DataRow ... issues involved with updating a primary key column value later in the section "Issues When Updating the Primary Key of a Parent Row." The ModifyingRelatedData.cs program contains a ... customersSelectCommand; customersDA.InsertCommand = customersInsertCommand; customersDA.UpdateCommand = customersUpdateCommand; Adding, Updating, and Deleting Related Rows In this section, you'll...
... ligand-binding domain; a transmembranedomain; an intracellular tyrosine kinase domain; and aC-terminal regulatory domain [2]. The extracellulardomain is subdivided further into four domains. ... EGFR(including EGF, transforming growth factor-a, amphi-regulin and epigen); (b) those that bind to EGFR andERBB4 (including betacellulin, heparin-binding EGFand epiregulin); and (c) neuregulin ... resulting in the overexpression of EGFRlacking amino acids 30–297, corresponding to domainsI and II. In this case, the EGFR tyrosine kinase is acti-vated constitutively without ligand binding,...
... compete with ATP for binding tothe tyrosine kinase pocket of the receptor, therebyinhibiting receptor tyrosine kinase activity and EGFRsignaling pathways (Fig. 1). Early clinical studiesshowed ... extracellular domain of the receptor,thereby inhibiting ligand-dependent EGFR signal transduction; and small-molecule tyrosine kinase inhibitors, such as gefitinib and erlotinib, whichtarget the intracellular ... results in EGFR signaling pathways beingturned off and the cancer cells undergoing apoptosis.Moreover, EGFR mutations result in repositioning ofcritical residues surrounding the ATP-binding cleft...
... CIP1is involved in gefitinib-induced growthinhibition in HNSCC [58]. Another group of cell-cycleregulatory molecules – those of the INK4 family – hasalso been implicated in gefitinib-induced inhibition ... consists of p15INK4b,p16INK4a, p18INK4cand p19INK4d.AG1478, which, like gefitinib and erlotinib, acts as aspecific inhibitor of the EGFR tyrosine kinase, hasbeen shown to result in a dose-dependent ... EGFR-targeting tyrosine kinase inhibitors(TKIs) in patients with NSCLC is closely associatedwith EGFR mutations such as del746-750 and L858R in the kinase domain [9–11]. Lung cancer cellsharboring...