Considerable work during the past two decades has focused on modeling the structure of semantic memory, although the performance of these models in complex and unconstrained semantic tasks remains relatively understudied. We introduce a two‐player cooperative word game, Connector (based on the boardgame Codenames), and investigate whether similarity metrics derived from two large databases of human free association norms, the University of South Florida norms and the Small World of Words norms, and two distributional semantic models based (...) on large language corpora (word2vec and GloVe) predict performance in this game. Participant dyads were presented with 20‐item word boards with word pairs of varying relatedness. The speaker received a word pair from the board (e.g., exam‐algebra) and generated a one‐word semantic clue (e.g., math), which was used by the guesser to identify the word pair on the board across three attempts. Response times to generate the clue, as well as accuracy and latencies for the guessed word pair, were strongly predicted by the cosine similarity between word pairs and clues in random walk‐based associative models, and to a lesser degree by the distributional models, suggesting that conceptual representations activated during free association were better able to capture search and retrieval processes in the game. Further, the speaker adjusted subsequent clues based on the first attempt by the guesser, who in turn benefited from the adjustment in clues, suggesting a cooperative influence in the game that was effectively captured by both associative and distributional models. These results indicate that both associative and distributional models can capture relatively unconstrained search processes in a cooperative game setting, and Connector is particularly suited to examine communication and semantic search processes. (shrink)

Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental lexicon. Network measures at different levels of analysis (degree, network distance, and closeness centrality) were used to investigate the influence of network structure on picture naming accuracy and errors by (...) people with Anomic, Broca's, Conduction, and Wernicke's aphasia. Our results reveal that word retrieval is influenced by the multiplex lexical network structure in at least two ways—(a) the accuracy of production and error type on incorrect productions were influenced by the degree and closeness centrality of the target word, and (b) error type also varied in terms of network distance between the target word and produced error word. Taken together, the analyses demonstrate that network science techniques, particularly the use of the multiplex lexical network to simultaneously represent semantic and phonological relationships among words, reveal how the structure of the mental lexicon influences language processes beyond traditionally examined psycholinguistic variables. We propose a framework for how the multiplex lexical network approach allows for understanding the influence of mental lexicon structure on word retrieval processes, with an eye toward a better understanding of the nature of clinical impairments, like aphasia. (shrink)

Recently, the pandemic caused by COVID-19 is severe in the entire world. The prevention and control of crimes associated with COVID-19 are critical for controlling the pandemic. Therefore, to provide efficient and convenient intelligent legal knowledge services during the pandemic, we develop an intelligent system for legal information retrieval on the WeChat platform in this paper. The data source we used for training our system is “The typical cases of national procuratorial authorities handling crimes against the prevention and control (...) of the new coronary pneumonia pandemic following the law”, which is published online by the Supreme People’s Procuratorate of the People’s Republic of China. We base our system on convolutional neural network and use the semantic matching mechanism to capture inter-sentence relationship information and make a prediction. Moreover, we introduce an auxiliary learning process to help the network better distinguish the relation between two sentences. Finally, the system uses the trained model to identify the information entered by a user and responds to the user with a reference case similar to the query case and gives the reference legal gist applicable to the query case. (shrink)

Searching through semantic memory may involve the use of several retrieval cues. In a verbal fluency task, the set of available cues is limited and every candidate word is a target. Individuals exhibit clustering behavior as predicted by optimal foraging theory. In another semantic search task, the remote associates task, three cues are presented and a single target word has to be found. Whereas the task has been widely studied as a task of creativity or insight problem (...) solving, in this article, the RAT is treated as a semantic retrieval task and assessed from the perspective of information foraging theory. Experiments are presented that address the superadditive combination of cues and the anti-clustering behavior in the recall sequence. A new type of search behavior in the RAT is put forward that involves maximizing the difference in activation between target and distractors. This type of search is advantageous when the target is weak and cue patches are contaminated with strong competitors. (shrink)

Barzykowski and Moulin's model proposes that déjà vu and involuntary autobiographical memories are the result of a continuously active memory system that tracks the novelty of situations. Déjà vu would only have episodic content and concern interpretation of prior experiences. We argue that these aspects of the model would gain to be clarified and explored further and we suggest possible directions.

Cognitive Science, Volume 46, Issue 6, June 2022.

Increasingly, taxonomies are being developed and used by industry practitioners to facilitate information interoperability and retrieval. Within a single industrial domain, there exist many taxonomies that are intended for different applications. Industry specific taxonomies often represent the vocabularies that are commonly used by the practitioners. Their jobs are multi-faceted, which include checking for code and regulatory compliance. As such, it will be very desirable if industry practitioners are able to easily locate and browse regulations of interest. In practice, multiple (...) sources of government regulations exist and they are often organized and classified by the needs of the issuing agencies that enforce them rather than the needs of the communities that use them. One way to bridge these two distinct needs is to develop methods and tools that enable practitioners to browse and retrieve government regulations using their own terms and vocabularies, for example, via existing industry taxonomies. The mapping from a single taxonomy to a single regulation is a trivial keyword matching task. We examine a relatedness analysis approach for mapping a single taxonomy to multiple regulations. We then present an approach for mapping multiple taxonomies to a single regulation by measuring the relatedness of concepts. Cosine similarity, Jaccard coefficient and market basket analysis are used to measure the semantic relatedness between concepts from two different taxonomies. Preliminary evaluations of the three relatedness analysis measures are performed using examples from the civil engineering and building industry. These examples illustrate the potential benefits of regulatory usage from the mapping between various taxonomies and regulations. (shrink)

Empirical studies indicate that analogy consists of two main processes: retrieval and mapping. While current theories and models of analogy have revealed much about the mainly structural constraints that govern the mapping process, the similarities that underpin the correspondences between individual representational elements and drive retrieval are understood in less detail. In existing models symbol similarities are externally defined but neither empirically grounded nor theoretically justified. This paper introduces a new model (EMMA: the environmental model of analogy) which (...) relies on co‐occurrence information provided by LSA (Latent Semantic Analysis; Landauer & Dumais, 1997) to ground the relations between the symbolic elements aligned in analogy. LSA calculates a contextual distribution for each word encountered in a corpus by counting the frequency with which it co‐occurs with other words. This information is used to define a model that locates each word encountered in a high‐dimensional space, with relations between elements in this space representing contextual similarities between words. A series of simulation experiments demonstrate that the environmental approach to semantics embodied in LSA can produce appropriate patterns of analogical retrieval, but that this semantic measure is not sufficient to model analogical mapping. The implications of these findings, both for theories of representation in analogy research and more general theories of semantics in cognition, are explored. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Retrieving Contuition in Saint BonaventureJunius Johnson (bio)Introduction: A Baffling ConceptThe word "contuition" is one that has an immediate effect on the reader who first encounters it in the pages of Bonaventure: it is evocative, teasing the reader with the promise of a rich and fresh, new way of thinking about knowledge. Thus, Raniero Sciamannini speaks of: "…that mysterious act of knowledge that, with a singular term, Saint Bonaventure has (...) called contuition and that has always excited such great perplexity among the interpreters. Is it a generic or specific term? An apprehension of things or of God? Abstract or intuitive? Mediate or immediate? Natural or supernatural?"1Contuitio is built on the verb tueor. And here it is clear that there is something common between "contuition" and its semantic relative "intuition," which is built on the same verb: both are forms of seeing. Since "intuition" is a more common word and concept, it will provide a good place to begin.Intuition, as most of the commentators see it, is an immediate gaze. It need not, however, be a comprehensive gaze. One may gaze immediately in apprehension as well.2 Apprehension is that gaze whereby one sees an object but one does not see all of the object. Apprehension is true, but incomplete. It is not necessarily veiled, or dark, though it may be these things. Rather, apprehension describes any instance in which the subject is incapable of seeing all of the object, whether this be from an impediment on the part of the object or the subject. Thus, in the case of my knowledge of a tree, which says more than I can hear and whose nature I only imperfectly grasp, my knowledge is apprehension because I see in a glass (under a veil) and darkly. And in the case of the knowledge the blessed have of God, it is also apprehension because God so greatly exceeds their capacity that they cannot exhaustively know God. [End Page 5]In one way of looking at it, all of our knowledge is only ever apprehensive: we never so exhaustively know a thing that we cannot come to know more about it (and this may be thought to be true eschatologically as well); this is one way of expressing the wonder and mystery of each particular thing. Underlying this understanding is a strong view of comprehension, one that holds that comprehensive knowing is the determinate and final knowledge of any thing. This is, however, not the sense that Bonaventure is working with. He will allow that we comprehend a tree, and thus apprehension is reserved for only those situations where some impediment or excess intervenes. In fact, in actual use, Bonaventure will tend to deploy apprehension in cases of excess, not impediment.Both intuitio and contuitio are often deployed to handle apprehensive knowledge, that is, real knowledge that nevertheless falls short of mastery, either because the knower does not attain to the whole of the thing, or because the knower is not capable of grasping the whole of the thing.That puts intuition and contuition in a similar field, but it does not yet really say what contuition is. It turns out to be quite difficult to get a straight answer about just what Bonaventure means by the term. Studies are not numerous: only about a dozen. Generally when the term is referenced outside of these studies, there is a tacit assumption that we already know what contuition means, or it is given a one sentence summary that clearly indicates that a deeper discussion is to be desired. For example, Leonard J. Bowman writes:The act of knowledge that achieves this apprehension of the Word through the creature, or the creature in the Word, involves a contuition. Contuition, within Bonaventure's symbolic theology, is a grasp of a perceived thing in relation to its causes, especially to its exemplary cause, the Word.3It is not so much that this is an untrue account (although it is limited, for it is unable to account for all of the uses of contuition in Bonaventure); rather, the problem is that it is a thin account. Bowman does not offer an argument for the... (shrink)

The associative theory of creativity states that creativity is associated with differences in the structure of semantic memory, whereas the executive theory of creativity emphasises the role of top-down control for creative thought. For a powerful test of these accounts, individual semantic memory structure was modelled with a novel method based on semantic relatedness judgements and different criteria for network filtering were compared. The executive account was supported by a correlation between creative ability and broad retrieval (...) ability. The associative account was independently supported, when network filtering was based on a relatedness threshold, but not when it was based on a fixed edge number or on the analysis of weighted networks. In the former case, creative ability was associated with shorter average path lengths and higher clustering of the network, suggesting that the semantic networks of creative people show higher small-worldness. (shrink)

1 Boolean retrieval 1 2 The term vocabulary and postings lists 19 3 Dictionaries and tolerant retrieval 49 4 Index construction 67 5 Index compression 85 6 Scoring, term weighting and the vector space model 109 7 Computing scores in a complete search system 135 8 Evaluation in information retrieval 151 9 Relevance feedback and query expansion 177 10 XML retrieval 195 11 Probabilistic information retrieval 219 12 Language models for information retrieval 237 13 (...) Text classification and Naive Bayes 253 14 Vector space classification 289 15 Support vector machines and machine learning on documents 319 16 Flat clustering 349 17 Hierarchical clustering 377 18 Matrix decompositions and latent semantic indexing 403 19 Web search basics 421 20 Web crawling and indexes 443 21 Link analysis 461.. (shrink)

In recent years, with the rapid development of computer storage capabilities and network transmission capabilities, users can easily share their own video and image information on social networking sites, and the amount of multimedia data on the network is rapidly increasing. With the continuous increase of the amount of data in the network, the establishment of effective automated data management methods and search methods has become an increasingly urgent need. This paper proposes a retrieval method of human motion data (...) based on motion capture in index space. By extracting key frames from the original motion to perform horizontal dimensionality reduction and defining features based on Laban motion analysis, the motion segment is subjected to vertical feature dimensionality reduction. After extracting features from the input motion segment, motion matching is performed on the index space. This paper designs the optimization method of the phased dynamic time deformation algorithm in time efficiency and analyzes the optimization method of the phased dynamic time deformation algorithm in time complexity. Considering the time efficiency redundancy, this paper optimizes the time complexity of the phased dynamic time deformation method. This improves the time efficiency of the staged dynamic time warping algorithm, making it suitable for larger-scale human motion data problems. Experiments show that the method in this paper has the advantage of speed, is more in line with the semantics of human motion, and can meet the retrieval requirements of human motion databases. (shrink)

A defining characteristic of Alzheimer’s disease is difficulty in retrieving semantic memories, or memories encoding facts and knowledge. While it has been suggested that this impairment is caused by a degradation of the semantic store, the precise ways in which the semantic store is degraded are not well understood. Using a longitudinal corpus of semantic fluency data, we derive semantic network representations of patients with Alzheimer’s disease and of healthy controls. We contrast our network-based approach (...) with analyzing fluency data with the standard method of counting the total number of items and perseverations in fluency data. We find that the networks of Alzheimer’s patients are more connected and that those connections are more randomly distributed than the connections in networks of healthy individuals. These results suggest that the semantic memory impairment of Alzheimer’s patients can be modeled through the inclusion of spurious associations between unrelated concepts in the semantic store. We also find that information from our network analysis of fluency data improves prediction of patient diagnosis compared to traditional measures of the semantic fluency task. (shrink)

There is no consensus as to whether a Liar sentence is meaningful or not. Still, a widespread conviction with respect to Liar sentences (and other ungrounded sentences) is that, whether or not they are meaningful, they are useless . The philosophical contribution of this paper is to put this conviction into question. Using the framework of assertoric semantics , which is a semantic valuation method for languages of self-referential truth that has been developed by the author, we show that (...) certain computational problems, called query structures , can be solved more efficiently by an agent who has self-referential resources (amongst which are Liar sentences) than by an agent who has only classical resources; we establish the computational power of self-referential truth . The paper concludes with some thoughts on the implications of the established result for deflationary accounts of truth. (shrink)

The main aim of the thesis is to give a semantic account of implicit content – the kind of content that plays a crucial role in implicit communication. Implicit communication is a species of communication in which a speaker communicates certain contents that go over and above the contents retrievable from the linguistic meaning of the words used. The focus of the thesis is a certain kind of implicit communication involving locations (when sentences such as “It is raining” are (...) used to communicate that it is raining at a certain location) and judges (when sentences such as “Avocado is tasty” are used to communicate that avocado is tasty for a certain person, called “the judge”). The way the topic of implicit content is approached is via the notion, widespread in contemporary philosophy of language, of “unarticulated constituents”. The thesis contains an investigation of this notion, with the specific aim of disentangling the many senses it has been used and of providing a general definition of the notion. A direct product of this investigation is a partitioning of the logical space; three positions are then selected, which correspond to the main contenders in the current debate involving unarticulated constituents: truth-conditional semantics, truth-conditional pragmatics and relativism. The biggest part of the thesis is dedicated to investigating certain arguments that have surfaced in the debate between these positions, with the ultimate goal of proposing a relativist account of implicit content. The particular version of relativism offered consists in the combination of the claim that locations and judges are part of the circumstances of evaluation, rather than the content of utterances, with “the variadic functions approach” to certain natural language expressions. Also, several arguments against a truth-conditional semantic approach to predicates of personal taste are provided. (shrink)

With the current changes driven by the expansion of the World Wide Web, this book uses a different approach from other books on the market: it applies ontologies to electronically available information to improve the quality of knowledge management in large and distributed organizations. Ontologies are formal theories supporting knowledge sharing and reuse. They can be used to explicitly represent semantics of semi-structured information. These enable sophisticated automatic support for acquiring, maintaining and accessing information. Methodology and tools are developed for (...) intelligent access to large volumes of semi-structured and textual information sources in intra- and extra-, and internet-based environments to employ the full power of ontologies in supporting knowledge management from the information client perspective and the information provider. The aim of the book is to support efficient and effective knowledge management and focuses on weakly-structured online information sources. It is aimed primarily at researchers in the area of knowledge management and information retrieval and will also be a useful reference for students in computer science at the postgraduate level and for business managers who are aiming to increase the corporations' information infrastructure. The Semantic Web is a very important initiative affecting the future of the WWW that is currently generating huge interest. The book covers several highly significant contributions to the semantic web research effort, including a new language for defining ontologies, several novel software tools and a coherent methodology for the application of the tools for business advantage. It also provides 3 case studies which give examples of the real benefits to be derived from the adoption of semantic-web based ontologies in "real world" situations. As such, the book is an excellent mixture of theory, tools and applications in an important area of WWW research. * Provides guidelines for introducing knowledge management concepts and tools into enterprises, to help knowledge providers present their knowledge efficiently and effectively. * Introduces an intelligent search tool that supports users in accessing information and a tool environment for maintenance, conversion and acquisition of information sources. * Discusses three large case studies which will help to develop the technology according to the actual needs of large and or virtual organisations and will provide a testbed for evaluating tools and methods. The book is aimed at people with at least a good understanding of existing WWW technology and some level of technical understanding of the underpinning technologies (XML/RDF). It will be of interest to graduate students, academic and industrial researchers in the field, and the many industrial personnel who are tracking WWW technology developments in order to understand the business implications. It could also be used to support undergraduate courses in the area but is not itself an introductory text. (shrink)

Instances in which we cannot retrieve information immediately but know that the information might be retrieved later are subjective states that accompany retrieval failure. These are expressed in feeling-of-knowing and Tip-of-the-tongue experiences. In Experiment 1, participants with Parkinson’s disease and older adult controls were given general questions and asked to report when they experienced a TOT state and to give related information about the missing word. The PD group experienced similar levels of TOTs but provided less correct peripheral information (...) related to the target when in a TOT state. In Experiment 2, participants were given a Semantic and an Episodic FOK task. PD patients failed to accurately predict their future memory performance in response to both episodic and semantic cues. Results are interpreted in the context of recent frameworks of memory and metacognition. (shrink)

Episodic memory often is conceptualized as a uniquely human system of long-term memory that makes available knowledge accompanied by the temporal and spatial context in which that knowledge was acquired. Retrieval from episodic memory entails a form of first–person subjectivity called autonoetic consciousness that provides a sense that a recollection was something that took place in the experiencer’s personal past. In this paper I expand on this definition of episodic memory. Specifically, I suggest that (a) the core features assumed (...) unique to episodic memory are shared by semantic memory, (b) episodic memory cannot be fully understood unless one appreciates that episodic recollection requires the coordinated function of a number of distinct, yet interacting, “enabling” systems. Although these systems – ownership, self, subjective temporality, and agency – are not traditionally viewed as memorial in nature, each is necessary for episodic recollection and jointly they may be sufficient, and (c) the type of subjective awareness provided by episodic recollection (autonoetic) is relational rather than intrinsic – i.e., it can be lost in certain patient populations, thus rendering episodic memory content indistinguishable from the content of semantic long-term memory. (shrink)

We show that vector space semantics and functional semantics in two-sorted first order logic are equivalent for pregroup grammars. We present an algorithm that translates functional expressions to vector expressions and vice-versa. The semantics is compositional, variable free and invariant under change of order or multiplicity. It includes the semantic vector models of Information Retrieval Systems and has an interior logic admitting a comprehension schema. A sentence is true in the interior logic if and only if the ‘usual’ (...) first order formula translating the sentence holds. The examples include negation, universal quantifiers and relative pronouns. (shrink)

Legal text retrieval traditionally relies upon external knowledge sources such as thesauri and classification schemes, and an accurate indexing of the documents is often manually done. As a result not all legal documents can be effectively retrieved. However a number of current artificial intelligence techniques are promising for legal text retrieval. They sustain the acquisition of knowledge and the knowledge-rich processing of the content of document texts and information need, and of their matching. Currently, techniques for learning information (...) needs, learning concept attributes of texts, information extraction, text classification and clustering, and text summarization need to be studied in legal text retrieval because of their potential for improving retrieval and decreasing the cost of manual indexing. The resulting query and text representations are semantically much richer than a set of key terms. Their use allows for more refined retrieval models in which some reasoning can be applied. This paper gives an overview of the state of the art of these innovativetechniques and their potential for legal text retrieval. (shrink)

In proposing that their model can operate in the concrete, perceptual world, Rogers & McClelland (R&M) have not done justice to the complexities of the ecological sphere and its invariance laws. The structure of concrete events forces a different framework, both for retrieval of events and concepts defined across events, than that upon which the proposed model, rooted in essence in the verbal learning tradition, implicitly rests.

The shriek modality \s! of linear logic performs two tasks: it restores in annotated from both weakening and contraction. We separate these tasks by introducing two modalities: for weakening and for contraction. These give rise to two logics which are “inbetween” linear and intuitionistic logic: in affine logic one always has a weakening and a for contraction and in relevant logic one always has a contraction and a weakening. The semantics of these logics is obtained from special kinds of monads, (...) introduced by Anders Kock in the early seventies. As subtle point is how to retrieve the \s! of linear logic from and . Technically this will be achieved in terms of distributive laws—introduced by Jon Beck. We find models where one has \s! = and also models with \s! = . It will be shown that on the category of complete lattices one has comonads and with = \s!=. (shrink)

When searching for concepts in memory—as in the verbal fluency task of naming all the animals one can think of—people appear to explore internal mental representations in much the same way that animals forage in physical space: searching locally within patches of information before transitioning globally between patches. However, the definition of the patches being searched in mental space is not well specified. Do we search by activating explicit predefined categories and recall items from within that category, or do we (...) activate and recall a connected sequence of individual items without using categorical information, with each item recalled leading to the retrieval of an associated item in a stream, or both? Using semantic representations in a search of associative memory framework and data from the animal fluency task, we tested competing hypotheses based on associative and categorical search models. Associative, but not categorical, patch transitions took longer to make than position-matched productions, suggesting that categorical transitions were not true transitions. There was also clear evidence of associative search even within categorical patch boundaries. Furthermore, most individuals' behavior was best explained by an associative search model without the addition of categorical information. Thus, our results support a search process that does not use categorical information, but for which patch boundaries shift with each recall and local search is well described by a random walk in semantic space, with switches to new regions of the semantic space when the current region is depleted. (shrink)

Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The model performs well on the task of retrieving the different meanings of ambiguous words, and is able to simulate data reported by Rodd, Gaskell, and Marslen‐Wilson [J. Mem. Lang. 46 (2002) (...) 245] on how semantic ambiguity affects lexical decision performance. In particular, the network shows a disadvantage forwords with multiple unrelated meanings (e.g., bark) that coexists with a benefit for words with multiple related word senses (e.g., twist). The ambiguity disadvantage arises because of interference between the different meanings, while the sense benefit arises because of differences in the structure of the attractor basins formed during learning. Words with few senses develop deep, narrow attractor basins, while words with many senses develop shallow, broad basins. We conclude that the mental representations of word meanings can be modelled as stable states within a high‐dimensional semantic space, and that variations in the meanings of words shape the landscape of this space. (shrink)

We discuss two key assumptions of Levelt et al.'s model of lexical retrieval: (1) the nondecompositional character of concepts and (2) lemmas as purely syntactic representations. These assumptions fail to capture the broader role of lemmas, which we propose as that of lexical–semantic representations binding (compositional) semantics with phonology (or orthography).

A large number of cross-references to various bodies of text are used in legal texts, each serving a different purpose. It is often necessary for authorities and companies to look into certain types of these citations. Yet, there is a lack of automatic tools to aid in this process. Recently, citation graphs have been used to improve the intelligibility of complex rule frameworks. We propose an algorithm that builds the citation graph from a document and automatically labels each edge according (...) to its purpose. Our method uses the citing text only and thus works only on citations who’s purpose can be uniquely identified by their surrounding text. This framework is then applied to the US code. This paper includes defining and evaluating a standard gold set of labels that cover a vast majority of citation types which appear in the “US Code” but are still short enough for practical use. We also proposed a novel linear-chain conditional random field model that extracts the features required for labeling the citations from the surrounding text. We then analyzed the effectiveness of different clustering methods such as K-means and support vector machine to automatically label each citation with the corresponding label. Besides this, we talk about the practical difficulties of this task and give a comparison of human accuracy compared to our end-to-end algorithm. (shrink)

This article is an exploratory study that intends to present semantic interoperability initiatives in the area of information science and computer science. It discusses these initiatives, focusing on open science and eScience, aiming at pointing out similarities and differences in the methodologies used for an intelligent retrieval of data in heterogeneous environments that do not benefit a universal language. We will illustrate seminal initiatives regarding the compatibility of languages in information science and the alignment and semantic mapping (...) in the area of computer science, emphasizing what they have in common and their differences, showing that those seminal initiatives are still relevant nowadays. In this perspective, we want to bring up discussions about methodologies that supports a kind of “intermediate language” that allows the compatibility of research resources, semantically interconnecting their contents without forcing the use of a single language, but of a switching language, such as a metalanguage that guarantees to keep the differences of each community of speech. (shrink)

The advent of digital cameras has provided photographers, with varying levels of expertise, the opportunity to accumulate large repositories of digital images. However, this expansion has also brought the attendant difficulty of image retrieval. This paper reviews the considerable work already carried out on image retrieval and identifies critical constraints in attempting to handle the underlying semantics of photographic images. The authors address the issue of how an amateur photographer, storing several thousand images a year, can effectively and (...) efficiently manage a personal collection. A number of surprisingly simple techniques are proposed utilising a sparse lexical ontology alongside iconic visual clues to identify key representative events in the collection. The photographer’s associated knowledge and experience, often shared by others who are attuned to the context of the collection, are critical to the effective management of the images. The authors recommend the use of existing browsers and a simple keyword table to facilitate concise and effective image storage and retrieval. Photographers can further enrich the representation of their collection by clustering images in accordance with their perceived relevance and aesthetic qualities. The authors argue that these properties can also be exploited to enhance retrieval. (shrink)