A graph-theoretic algorithm for automatic extension of translation lexicons

Abstract

This paper presents a graph-theoretic approach to the identification of yetunknown word translations. The proposed algorithm is based on the recursive Sim-Rank algorithm and relies on the intuition that two words are similar if they establish similar grammatical relationships with similar other words. We also present a formulation of SimRank in matrix form and extensions for edge weights, edge labels and multiple graphs.

A survey of graphs in natural language processing

“…Semantic orientation can be transferred between languages using graph alignments. Scheible et al (2010) build monolingual sentiment graphs for the source and target language respectively, and then align nodes in the two graphs based on a similarity measure that relies on the topology of each graph and a set of seed links between them, as in the SimRank algorithm (Jeh and Widom 2002; Dorow et al 2009). The influence of different phenomena (coordinations through ‘and’ and ‘but’, adjective-noun modification) can be computed separately and then averaged to obtain the final similarity score for two compared nodes.…”

CoSimRank: A Flexible and Efficient Graph-Theoretic Similarity Measure

“…We often want to compute the similarity of nodes in two different graphs with a known node-node correspondence; this is the scenario we are faced with in the lexicon extraction task (see Section 6). A variant of SimRank for this task was presented by Dorow et al (2009). We will now present an equivalent method for CoSimRank.…”

“…A variant of SimRank for this task was presented by Dorow et al (2009). We will now present an equivalent method for CoSimRank.…”

“…Consequently, we compare against the two main methods for this task in NLP: SimRank and extensions of PageRank. We also compare against the MEE (Multi-Edge Extraction) variant of SimRank (Dorow et al, 2009), which handles labeled edges more efficiently than SimRank:…”

“…Dorow et al (2009) and extend SimRank to edge weights, edge labels and multiple graphs. We use their Multi-Edge Extraction (MEE) algorithm as one of our baselines below.…”