MAC/FAC: A Model of Similarity-Based Retrieval

Forbus, Kenneth D.; Gentner, Dedre; Law, Keith

doi:10.21236/ada286291

Cited by 29 publications

(52 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[6, chs. 8-10], and also [7]) our architecture (see Fig. 2) supports a two-stage process for diagram retrieval: reminding (or initial recall), and selection.…”

Section: The Retrieval Taskmentioning

confidence: 80%

“…MAC/FAC [7] is a well-known model of two-stage analogical retrieval and mapping based on the Structure Mapping Engine (SME) [12]. It employs a heuristic much like our feature vectors for the first stage, computing "content vectors" for each source analog in memory that count the object attributes and higher-order relations contained in the description.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Visual analogy: Viewing analogical retrieval and mapping as constraint satisfaction problems

Yaner

Goel

2006

Appl Intell

View full text Add to dashboard Cite

The core issue of analogical reasoning is the transfer of relational knowledge from a source case to a target problem. Visual analogical reasoning pertains to problems containing only visual knowledge. Holyoak and Thagard proposed that the retrieval and mapping tasks of analogy in general can be productively viewed as constraint satisfaction problems, and provided connectionist implementations of their proposal. In this paper, we reexamine the retrieval and mapping tasks of analogy in the context of diagrammatic cases, representing the spatial structure of source and target diagrams as semantic networks in which the nodes represent spatial elements and the links represent spatial relations. We use a method of constraint satisfaction with backtracking for the retrieval and mapping tasks, with subgraph isomorphism over a particular domain language as the similarity measure. Results in the domain of 2D line drawings suggest that at least for this domain the above method is quite promising.

show abstract

“…[6, chs. 8-10], and also [7]) our architecture (see Fig. 2) supports a two-stage process for diagram retrieval: reminding (or initial recall), and selection.…”

Section: The Retrieval Taskmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Visual analogy: Viewing analogical retrieval and mapping as constraint satisfaction problems

Yaner

Goel

2006

Appl Intell

View full text Add to dashboard Cite

show abstract

“…Recently, a probabilistic similarity model for workflow execution paths was also proposed (Becker, Bergener, Breuker, & Räckers, 2011). Other approaches have suggested the use of a two-step procedure, which combines an initial and comparatively inexpensive retrieval step, to winnow the instances to be considered, with a more expensive strategy that ranks the remaining instances (as in the well-known MAC/FAC system (Forbus, Gentner, & Law, 1995)) (KendallMorwick & Leake, 2011. In Bergmann and Gil (2014), some procedures for non-exhaustive search, based on the A ⁄ algorithm, are provided.…”

Section: Related Workmentioning

confidence: 99%

A knowledge-intensive approach to process similarity calculation

Montani¹,

Leonardi²,

Quaglini³

et al. 2015

Expert Systems with Applications

View full text Add to dashboard Cite

“…We will have more to say on this later in this article.) Nearly all computational models rely on a process whereby hierarchies or graphs are matched on the basis of similarity (shared features and shared relations), empty feature slots are filled by a process of mapping or filtering, or there is some process of restructuring of relations (Burns, 1995;Forbus, Gentner, & Law, 1995;Hall, 1988;Holyoak, Novick, & Melz, 1994;Markman & Gentner, 2000). AI models include other techniques, such as constraint satisfaction (Thagard, Holyoak, Nelson, & Gochfeld, 1990).…”

Section: Analogy and Computer Sciencementioning

confidence: 99%

A Naturalistic Exploration of Forms and Functions of Analogizing

Hoffman

Eskridge

Shelley

2009

Metaphor and Symbol

View full text Add to dashboard Cite

The purpose of this article is to invigorate debate concerning the nature of analogy, and to broaden the scope of current conceptions of analogy. We argue that analogizing is not a single or even a fundamental cognitive process. The argument relies on an analysis of the history of the concept of analogy, case studies on the use of analogy in scientific problem solving, cognitive research on analogy comprehension and problem solving, and a survey of computational mechanisms of analogy comprehension. Analogizing is regarded as a macrocognitive phenomenon having a number of supporting processes. These include the apperception of resemblances and distinctions, metaphor, and the balancing of semantic flexibility and inference constraint. Psychological theories and computational models have generally relied on (a) a sparse set of ontological concepts (a property called "similarity" and a structuralist categorization of types of semantic relations), (b) a single form category (i.e., the classic four-term analogy), and (c) a single set of morphological distinctions (e.g., verbal vs. pictorial analogies). This article presents a classification based on a "naturalistic" exploration of the variety of uses of analogical reasoning in pragmatically distinct contexts. The resultant taxonomy distinguishes pre-hoc, ad-hoc, post-hoc, pro-hoc, contra-hoc, and trans-hoc analogy. Each will require its own macrocognitive modeling, and each presents an opportunity for research on phenomena of reasoning that have been neglected.

show abstract

MAC/FAC: A Model of Similarity-Based Retrieval

Abstract: Puojbc reoorting ouraen for this c e(tontt )t formaton o S est atno to averat e S"our per resporse. ,~luOdng the time 4or reviewing istructiOns. searchtng existing data sources, ga theremg and mtant.3jC ng the data needed, ani con-peting and rev,

Cited by 29 publications

References 38 publications

Visual analogy: Viewing analogical retrieval and mapping as constraint satisfaction problems

Visual analogy: Viewing analogical retrieval and mapping as constraint satisfaction problems

A knowledge-intensive approach to process similarity calculation

A Naturalistic Exploration of Forms and Functions of Analogizing

Contact Info

Product

Resources

About