Representing word meaning and order information in a composite holographic lexicon.

By Michael N. Jones, D. Mewhort. Psychology Review, 2007

632 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/d3cf28ab36ff7f7601a55c1e832736b2473a07f0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Developmental and Educational Psychology

Citations in the corpus

Vector Space Models of Word Meaning and Phrase Meaning: A Survey (2012, background): “Jones and Mewhort (2007) construct vectors for word n-grams, and then derive the vector for a target word w as the superposition (addition) of n-gram vectors for observed contexts of w.”
Distributional semantics in linguistic and cognitive research (2008, background): “…show that, although many problems still remain to be solved, compositionality is indeed an aspect of meaning that can in principle be tackled with contextual representations, and actually this is an important issue in the agenda of distributional semantics nowadays (cf. also Jones & Mewhort 2007).”
Design for a working memory. (2009, neutral): “With distributed representations (i.e., each content component is represented by a pattern of activation across many units), the new chunk could be represented by a new pattern created from its component patterns, for instance, by circular convolution ( Jones & Mewhort, 2007; Plate, 2003).”
Optimal foraging in semantic memory. (2012, methodology): “Two sources are used to represent the semantic space searched in the fluency task: hand-coded categorizations from Troyer, Moscovitch, & Winocur (1997) and lexical semantic representations from BEAGLE, a corpus-based semantic space model (Jones & Mewhort, 2007).”
WordICA—emergence of linguistic representations for words by independent component analysis (2010, positive): “Moreover, it is also worth while to study how encoding the relative position of terms in a sliding window inﬂuences the results of the analysis (Jones and Mewhort 2007; Sahlgren, Holst and Kanerva 2008).”
Hyperdimensional Computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors (2009, neutral): “Jones and Mewhort [27] do it with circular convolution applied to real-valued HRR-vectors, Sahlgren et al. [28] do it with permutations applied to ternary random-index vectors.”
Estimating Linear Models for Compositional Distributional Semantics (2010, methodology): “On the other hand, compositional distributional semantics (CDS) propose to obtain distributional meaning for sequences by composing the vectors of the words in the sequences (Mitchell and Lap-ata, 2008; Jones and Mewhort, 2007).”
Domain and Function: A Dual-Space Model of Semantic Relations and Compositions (2012, background): “Circular convolution is similar to the outer product, but the outer product matrix is compressed back down to a vector, c = a ⊛ b (Plate, 1995; Jones & Mewhort, 2007).”
Nouns are Vectors, Adjectives are Matrices: Representing Adjective-Noun Constructions in Semantic Space (2010, background): “…encompasses various related topics, some of them not of direct interest here, such as how to encode word order information in context vectors (Jones and Mewhort, 2007; Sahlgren et al., 2008) or sophisticated composition methods based on tensor products, quantum logic, etc., that have not yet…”
Distributional Memory: A General Framework for Corpus-Based Semantics (2010, neutral): “…research areas such as neural systems (Smolensky 1990; Smolensky and Legendre 2006), quantum information (Widdows and Peters 2003; Aerts and Czachor 2004; Widdows 2004; Van Rijsbergen 2004; Bruza and Cole 2005; Hou and Song 2009), holographic models of memory (Jones and Mewhort 2007), and so on.”
Enhancing clinical concept extraction with distributional semantics (2011, methodology): “This method is an alternative implementation to the convolution operations used by BEAGLE [49] (based on Tony Plate’s Holographic Reduced Representation (HRR) [50]) to encode word-order information in word spaces.”
Combining Distributed Vector Representations for Words (2015, methodology): “DVRS (Ustun et al., 2014) is a method for generating semantic vector representations based on ideas introduced in Jones and Mewhort (2007)’s BEAGLE system.”
Biologically Plausible, Human-scale Knowledge Representation (2016, methodology): “They have seen significant use in cognitive modeling; for instance, Murdock (1993) uses HRRs to provide an account of human working memory, and Jones and Mewhort (2007) use them to construct vector-space representations of English words from text, which are able to account for a number of classic em”
Composition in Distributional Models of Semantics (2010, methodology): “Jones and Mewhort (2007) propose a model that makes use of the linear order of words in a context.”