[PDF] Top 20 The Lifted Matrix Space Model for Semantic Composition
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The Lifted Matrix Space Model for Semantic Composition
... Figure 2 depicts the corresponding confusion matrices for the 19-way classification task. We show the most frequent eight classes due to space limitations. We observe notable gains on adver- bial phrases (ADVP; ... See full document
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Language Models Based on Semantic Composition
... n-gram model (see equation ...multiplicative composition functions, and two semantic representations (LDA and the sim- pler semantic space model), resulting in four com- ... See full document
10
Semantic Composition via Probabilistic Model Theory
... Semantic composition involves taking semantic representations for multiple expressions, and combining them into a single representation for the whole ...vector space models, this involves map- ... See full document
16
Structured Composition of Semantic Vectors
... vectorial semantic framework, in which semantic vectors are defined and composed in syntactic ...interactive; composition of semantic vectors necessarily produces a hypothetical syntactic ...a ... See full document
10
Measuring Distributional Similarity in Context
... simple semantic space (see SVS in Table ...multiplicative model using a simple semantic space (Mult-SVS) is the best performing compositional model, thus corroborating the ... See full document
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A Systematic Study of Semantic Vector Space Model Parameters
... Previous studies have been limited to investigat- ing only a small number of parameters, and us- ing a limited set of source corpora and tasks for evaluation (Curran and Moens, 2002a; Curran and Moens, 2002b; Curran, ... See full document
10
A Compositional and Interpretable Semantic Space
... scoring model, CNNSE, only identi- fies the correct phrase for 26% of the test ...a model makes a “mistake”, it is possible that the top-ranked phrase is a synonym of, or closely related to, the actual ... See full document
10
Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition
... Our MEG data was collected while 9 partici- pants viewed 38 phrases, each repeated 20 times (randomly interleaved). The stimulus nouns were chosen because previous research had shown them to be decodable from MEG ... See full document
10
Image Classification Based on Effective Probabilistic Latent Semantic Analysis Model
... In previous works the classification has been done based on spectral and textural features of the rocks [8].The spectral features are considered as some color parameters whereas the textural features are calculated from ... See full document
7
Measuring the Similarity between Automatically Generated Topics
... distributional semantic metric using the Topic Word Space (RCS-Cos-TWS) is com- parable and slightly lower for the top-N features ...of semantic subjects than the latent space produced by the ... See full document
6
Composition of Semantic Relations: Model and Applications
... Objects can be either concrete or abstract . The former occupy space, are touchable and tangi- ble. The latter are intangible; they are somehow a product of human reasoning. Concrete objects are further divided ... See full document
9
A Generalisation of Lexical Functions for Composition in Distributional Semantics
... a matrix; the vector captures the actual mean- ing of the constituent, while the matrix models the way it changes the meaning of neighbouring words and ...the model for a sentiment prediction task. ... See full document
11
Semantic Composition with Quotient Algebras
... the space of adjective/noun phrases, generated by N 0 , and define the individual context of a noun to be the verb it occurs with, and the in- dividual context of an adjective to be the noun it ...vector ... See full document
7
Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words
... vector space represented by the distributed representa- ...Markov model (HMM) based speech recognition (Grezl and Fousek, ...topic model (BTM) (Yan et ... See full document
9
Community Matrix Model Predictions of Future Forest Composition at Russell State Forest
... SUMMARY: The data of Lloyd (1971) on the 'chosen tree' and 'chosen seedlings' in 5607 4 x 4 m plots in Russell forest are analysed using a simple transition matrix model. The most realistic analysis ... See full document
7
End to End Feature Aware Label Space Encoding for Multilabel Classification With Many Classes
... predictive model for each label independently or with inter- label correlations, and then combine them in a certain manner for ...label space), the number of needed predictive models would generally be ... See full document
20
A Calculus for Semantic Composition and Scoping
... Instead of trying to construct a type system and type rules such that free application of the rules starting from appropriate lexical axioms will generate all and only the possible meani[r] ... See full document
9
Biased-Incremental Clustering: A Flexible Knowledge Extraction Algorithm
... Tables 1, 2 and 3 show how the Biased-Incremental Clustering approach is used to build and refine a knowledge-base. The Sci-Med sub-dataset of the 20 Newsgroups Datasets [11] was used. Table 1 shows how relevant terms ... See full document
5
Web Clustering Based On Tag Set Similarity
... vector space model, which takes into account patterns of term co-occurrence and is efficient enough to be of practical ...The model exploits the intuition that semantically related terms often occur ... See full document
8
On Equivalence of Quantum Liouville Equation and Metric Compatibility Condition, a Ricci Flow Approach
... projection matrix with non-zero element at row “i” and column ...density matrix represents the population (probability) of a specific basis (state) therefore the trace of density matrix is ...density ... See full document
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