There are at least two kinds of similarity. Relational similarity is correspondence between relations, in contrast with attributional similarity, which is correspondence between attributes. When two words have a high degree of attributional similarity, we call them synonyms. When two pairs of words have a high degree of relational similarity, we say that their relations are analogous. For example, the word pair mason:stone is analogous to the pair carpenter:wood. This paper introduces Latent Relational Analysis (LRA), a method for measuring relational similarity. LRA has potential applications in many areas, including information extraction, word sense disambiguation, and information retrieval. Recently the Vector Space Model (VSM) of information retrieval has been adapted to measuring relational similarity, achieving a score of 47 on a collection of 374 college-level multiple-choice word analogy questions. In the VSM approach, the relation between a pair of words is characterized by a vector of frequencies of predefined patterns in a large corpus. LRA extends the VSM approach in three ways: (1) the patterns are derived automatically from the corpus, (2) the Singular Value Decomposition (SVD) is used to smooth the frequency data, and (3) automatically generated synonyms are used to explore variations of the word pairs. LRA achieves 56 on the 374 analogy questions, statistically equivalent to the average human score of 57 . On the related problem of classifying semantic relations, LRA achieves similar gains over the VSM.
Metaphorical language is very common in our daily life; so common that we are usually unaware of it @cite_46 . gentner01 argue that novel metaphors are understood using analogy, but conventional metaphors are simply recalled from memory. A conventional metaphor is a metaphor that has become entrenched in our language @cite_46 . dolan95 describes an algorithm that can recognize conventional metaphors, but is not suited to novel metaphors. This suggests that it may be fruitful to combine Dolan's algorithm for handling conventional metaphorical language with LRA and SME for handling novel metaphors.
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CorMet is a corpus-based system for discovering metaphorical mappings between concepts. It does this by finding systematic variations in domain-specific selectional preferences, which are inferred from large, dynamically mined Internet corpora.Metaphors transfer structure from a source domain to a target domain, making some concepts in the target domain metaphorically equivalent to concepts in the source domain. The verbs that select for a concept in the source domain tend to select for its metaphorical equivalent in the target domain. This regularity, detectable with a shallow linguistic analysis, is used to find the metaphorical interconcept mappings, which can then be used to infer the existence of higher-level conventional metaphors.Most other computational metaphor systems use small, hand-coded semantic knowledge bases and work on a few examples. Although CorMet's only knowledge base is WordNet (Fellbaum 1998) it can find the mappings constituting many conventional metaphors and in some cases recognize sentences instantiating those mappings. CorMet is tested on its ability to find a subset of the Master Metaphor List (Lakoff, Espenson, and Schwartz 1991). This article explores the application of metaphors in news headlines with a view to interrogating their potential for coercion. Coercion in news discourse is understood as a strategic deployment of pragma-linguistic devices, including metaphors, to foreground the representations of socio-political reality that are compatible with the interests of the news outlet rather than those that inform public debate. It is argued that coercion can be exposed through systematic discourse analysis. Methodologically, the study aims to integrate the cognitive and pragmatic approaches to metaphor in regarding it as both a conceptual building block of news representations and a strategic framing device in news discourse. A quantitative and qualitative analysis of a sample of metaphors excerpted from a corpus of 400 most-read headlines from one of the most visited English-language newspaper sites The Daily Mail is conducted to illustrate such coercive applications of metaphor as simplification, imaging, animalization, confronta tion, (de)legitimization, emotionalization, and dramatization. In the course of the analysis it is demonstrated how certain ideologically-biased representations can be coerced through figurative language. People use metaphors every time they speak. Some of those metaphors are literary - devices for making thoughts more vivid or entertaining. But most are much more basic than that - they're "metaphors we live by", metaphors we use without even realizing we're using them. In this book, George Lakoff and Mark Johnson suggest that these basic metaphors not only affect the way we communicate ideas, but actually structure our perceptions and understandings from the beginning. Bringing together the perspectives of linguistics and philosophy, Lakoff and Johnson offer an intriguing and surprising guide to some of the most common metaphors and what they can tell us about the human mind. And for this new edition, they supply an afterword both extending their arguments and offering a fascinating overview of the current state of thinking on the subject of the metaphor. Conventional software systems, such as those based on the “desktop metaphor,” are ill-equipped to manage the electronic information and events of the typical computer user. We introduce a new metaphor, Lifestreams, for dynamically organizing a user's personal workspace. Lifestreams uses a simple organizational metaphor, a time-ordered stream of documents, as an underlying storage system. Stream filters are used to organize, monitor and summarize information for the user. Combined, they provide a system that subsumes many separate desktop applications. This paper describes the Lifestreams model and our prototype system.