13,639 research outputs found
The Latent Relation Mapping Engine: Algorithm and Experiments
Many AI researchers and cognitive scientists have argued that analogy is the
core of cognition. The most influential work on computational modeling of
analogy-making is Structure Mapping Theory (SMT) and its implementation in the
Structure Mapping Engine (SME). A limitation of SME is the requirement for
complex hand-coded representations. We introduce the Latent Relation Mapping
Engine (LRME), which combines ideas from SME and Latent Relational Analysis
(LRA) in order to remove the requirement for hand-coded representations. LRME
builds analogical mappings between lists of words, using a large corpus of raw
text to automatically discover the semantic relations among the words. We
evaluate LRME on a set of twenty analogical mapping problems, ten based on
scientific analogies and ten based on common metaphors. LRME achieves
human-level performance on the twenty problems. We compare LRME with a variety
of alternative approaches and find that they are not able to reach the same
level of performance.Comment: related work available at http://purl.org/peter.turney
Automated Generation of Cross-Domain Analogies via Evolutionary Computation
Analogy plays an important role in creativity, and is extensively used in
science as well as art. In this paper we introduce a technique for the
automated generation of cross-domain analogies based on a novel evolutionary
algorithm (EA). Unlike existing work in computational analogy-making restricted
to creating analogies between two given cases, our approach, for a given case,
is capable of creating an analogy along with the novel analogous case itself.
Our algorithm is based on the concept of "memes", which are units of culture,
or knowledge, undergoing variation and selection under a fitness measure, and
represents evolving pieces of knowledge as semantic networks. Using a fitness
function based on Gentner's structure mapping theory of analogies, we
demonstrate the feasibility of spontaneously generating semantic networks that
are analogous to a given base network.Comment: Conference submission, International Conference on Computational
Creativity 2012 (8 pages, 6 figures
Niche as a determinant of word fate in online groups
Patterns of word use both reflect and influence a myriad of human activities
and interactions. Like other entities that are reproduced and evolve, words
rise or decline depending upon a complex interplay between {their intrinsic
properties and the environments in which they function}. Using Internet
discussion communities as model systems, we define the concept of a word niche
as the relationship between the word and the characteristic features of the
environments in which it is used. We develop a method to quantify two important
aspects of the size of the word niche: the range of individuals using the word
and the range of topics it is used to discuss. Controlling for word frequency,
we show that these aspects of the word niche are strong determinants of changes
in word frequency. Previous studies have already indicated that word frequency
itself is a correlate of word success at historical time scales. Our analysis
of changes in word frequencies over time reveals that the relative sizes of
word niches are far more important than word frequencies in the dynamics of the
entire vocabulary at shorter time scales, as the language adapts to new
concepts and social groupings. We also distinguish endogenous versus exogenous
factors as additional contributors to the fates of words, and demonstrate the
force of this distinction in the rise of novel words. Our results indicate that
short-term nonstationarity in word statistics is strongly driven by individual
proclivities, including inclinations to provide novel information and to
project a distinctive social identity.Comment: Supporting Information is available here:
http://www.plosone.org/article/fetchSingleRepresentation.action?uri=info:doi/10.1371/journal.pone.0019009.s00
The Effectiveness of Case-Based Reasoning: An Application in Sales Promotions
This paper deals with Case-based Reasoning (CBR) as a support technology for sales promotion (SP) decisions. CBR-systems try to mimic analogical reasoning, a form of human reasoning that is likely to occur in weakly-structured problem solving, such as the design of sales promotions. In an empirical study, we find evidence that use of the CBR-system improves the quality of SP-campaign proposals. In terms of the creativity of the proposals, decision-makers who think highly divergent (i.e., who tend to generate many, and diverse ideas in response to a problem) benefit most from prolonged system usage. Creativity, in turn, is positively related to the (practical) usability of a proposal. These results suggest that the CBR-system is most effective when it is used as an idea-generation tool that reinforces the strength of divergent (creative) thinkers. A convergent thinking style, in which case the CBR-system has a compensating role, even has a negative impact on CBR-system usage. Increasing the decision-maker's personal belief in the usefulness of the system, e.g., by training or education, may help to alleviate this reluctance to use the CBR-system.marketing management support systems;sales promotions;case-based reasoning;weakly-structured decision making
Specialization of the rostral prefrontal cortex for distinct analogy processes
Analogical reasoning is central to learning and abstract thinking. It involves using a more familiar situation (source) to make inferences about a less familiar situation (target). According to the predominant cognitive models, analogical reasoning includes 1) generation of structured mental representations and 2) mapping based on structural similarities between them. This study used functional magnetic resonance imaging to specify the role of rostral prefrontal cortex (PFC) in these distinct processes. An experimental paradigm was designed that enabled differentiation between these processes, by temporal separation of the presentation of the source and the target. Within rostral PFC, a lateral subregion was activated by analogy task both during study of the source (before the source could be compared with a target) and when the target appeared. This may suggest that this subregion supports fundamental analogy processes such as generating structured representations of stimuli but is not specific to one particular processing stage. By contrast, a dorsomedial subregion of rostral PFC showed an interaction between task (analogy vs. control) and period (more activated when the target appeared). We propose that this region is involved in comparison or mapping processes. These results add to the growing evidence for functional differentiation between rostral PFC subregions
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Rationality in context: An analogical perspective
At times, human behavior seems erratic and irrational. Therefore, when modeling human decision-making, it seems reasonable to take the remarkable abilities of humans into account with respect to rational behavior, but also their apparent deviations from the normative standards of rationality shining up in certain rationality tasks. Based on well-known challenges for human rationality, together with results from psychological studies on decision-making and from previous work in the field of computational modeling of analogy-making, I argue that the analysis and modeling of rational belief and behavior should also consider context-related cognitive mechanisms like analogy-making and coherence maximization of the background theory. Subsequently, I conceptually outline a high-level algorithmic approach for a Heuristic Driven Theory Projection-based system for simulating context-dependent human-style rational behavior. Finally, I show and elaborate on the close connections, but also on the significant differences, of this approach to notions of "ecological rationality"
When Intelligence is (Dys)Functional for Achieving Sales Performance
Using two different samples of salespeople, the authors investigate how a combination of general mental ability (GMA) and specific skills and capabilities (social competence and thinking styles) allows salespeople to reach their sales goals. The study finds evidence for an interaction between GMA and social competence. If combined with high social competence, high GMA leads to highest sales performance; if combined with low social competence, high GMA leads to lowest sales performance. In addition, interaction effects between GMA and a judicial thinking style were found. Salespeople high on GMA have the most potential for attaining high levels of sales performance when combined with specific skills; when lacking these skills they may become the firm’s worst performers.sales;knowledge;general mental ability;knowledge based marketing;thinking styles
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