[PDF] Top 20 Feature Vector Quality and Distributional Similarity

... Distributional Similarity has been an active re- search area for more than a decade (Hindle, 1990), (Ruge, 1992), (Grefenstette, 1994), (Lee, 1997), (Lin, 1998), (Dagan et ...Harris distributional ... See full document

... of distributional similarity measures to model entailing lexical substitutions (Jijkoun and de Rijke 2005; Adams 2006; Ferrandez et ...the distributional information typically complements man- ual ... See full document

... construct distributional thesauri, the contexts in which a target word appears in a sentence or document can be de- fined in terms of a window of co-occurring (content) words surrounding the target (Freitag et ... See full document

... based feature extractor is ...a vector of features. The RMM model determines feature vectors for all input images and undergone a comparison with features exist in ...highest similarity are ... See full document

... tributional similarity models to effectively lever- age larger word window contexts for measuring semantic ...simple feature vector models reach near-optimal performance with small word win- dows of ... See full document

... improve distributional measures of seman- tic similarity at the sentence ...the distributional features before factorization, so that discriminability impacts the induction of the la- tent ...sample ... See full document

... constructed similarity matrices by using the characteristic map of first- and second-order Riesz transforms and utilized edge features as pooling func- tion to derive the RFSIM index because of the good ... See full document

... verb’s vector with the vector capturing the inverse selectional preferences of the object; the latter are computed as the centroid of the verbs that occur with this ...its vector to the features ... See full document

... noun similarity in DTs. Second, we have explored how to improve DT quality by combining features from several ...semantic similarity, especially for nouns, is a building block for many NLP ... See full document

... and similarity calcula- tion are two essential features of a distri- butional similarity scheme ...the distributional similar- ities among the top-ranked relation ...pairwise similarity ... See full document

... To tackle this issue, Curran and Moens (2002b) suggest assigning an index vector of canonical at- tributes, i.e., a small number of representative el- ements extracted from the original vector, to each ... See full document

... cluster agglomeration and the inter-cluster distinctness. Precisions of Spectral Clustering, Graph Clustering, SOM, and GHSOM are lower than VCLC. These four algorithms all map a high dimensional data space into a low ... See full document

... is given. This baseline tests possible memoriza- tion effects (Levy et al., 2015). For instantiation, we have a third baseline, Cap. It makes a rule- based decision on the basis of capitalization where available and ... See full document

... The main limitation of the PCA is that it searches for the features which their sample's value have bigger variance in comparison with others, and it does not collaborate with the classifier. So, for overcoming this ... See full document

... We presented a method for the extraction of synonyms for German particle verbs using parallel data. In order to deal with separated particles, we applied reordering rules to the German part of the data. In our ... See full document

... As shown above, semantic drift still dominates the later iterations of bootstrapping even after bag- ging. In this section, we propose distributional similarity measurements over the extracted lexi- con to ... See full document

... Harris’ distributional hypothesis to relations, as well as recent ad- vances in learning text representations (specif- ically, BERT), to build task agnostic relation representations solely from entity-linked ... See full document

... counts of all words/word pairs in fixed amount of main memory. We used conservative update with CM sketch (referred as CU sketch) and showed that it reduces the average relative error of its ap- proximate counts by a ... See full document

... a similarity measure amongst the employees and use it to form coherent clusters based on their field of ...this similarity measure is inversely proportional to the element wise difference between two such ... See full document

... tors are used to compose the PSC -based vectors 2 of the compound. Related work to ours is (Reisinger and Mooney, 2010) where exemplars of a word are first clustered and then prototype vectors are built. This work does ... See full document