Online research in philosophy

Carruthers’ notion that natural language(s) might serve as the medium of non-domain-specific, propositionally based inferential thought is extended to the case of effortful retrieval of autobiographical memory among bilinguals. Specifically, the review suggests that the resources of bilingual inner speech might play a role in the cyclical activation of information from various informational domains during memory retrieval.

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..

Pickering & Garrod's (P&G's) interactive alignment model explains the existence of alignment between speakers via an automatic priming mechanism. We propose that it may be preferable to explain alignment through processes of memory retrieval. Our discussion highlights how memory retrieval can produce the same results as the priming mechanism and presents data that favor the memory-based view.

The ability to find relevant materials in large document collections is a fundamental component of legal research. The emergence of large machine-readable collections of legal materials has stimulated research aimed at improving the quality of the tools used to access these collections. Important research has been conducted within the traditional information retrieval, the artificial intelligence, and the legal communities with varying degrees of interaction between these groups. This article provides an introduction to text retrieval and surveys the main research related to the retrieval of legal materials.

69 Thompson-Schill, S.L. _et al. _(1997) Role of left inferior prefrontal cortex 59 Buckner, R.L. _et al. _(1996) Functional anatomic studies of memory in retrieval of semantic knowledge: a re-evaluation _Proc. Natl. Acad._ retrieval for auditory words and pictures _J. Neurosci. _16, 6219–6235 _Sci. U. S. A. _94, 14792–14797 60 Buckner, R.L. _et al. _(1995) Functional anatomical studies of explicit and 70 Baddeley, A. (1992) Working memory: the interface between memory implicit memory retrieval tasks _J. Neurosci. _15, 12–29 and cognition _J. Cogn. Neurosci. _4, 281–288 61 Bäckman, L. _et al. _(1997) Brain activation in young and older adults 71 Petrides, M. (1994) Frontal lobes and behavior _Curr. Opin. Neurobiol._ during implicit and explicit retrieval _J. Cogn. Neurosci. _9, 378–391.

This paper looks at the epistemological foundations of knowledge representations embodied in retrieval languages. It considers questions such as the validity of knowledge representations and their effectiveness for the purposes of retrieval and automation. The knowledge representations it considers are derived from three theories of meaning that have dominated twentieth-century philosophy.

Legal information retrieval is in need of the provision of legal knowledge for the improvement of search strategies. For this purpose, the LOIS project is concerned with the construction of a multilingual WordNet for cross-lingual information retrieval in the legal domain. In this article, we set out how a hybrid approach, featuring lexically and legally grounded conceptual representations, can fit the cross-lingual information retrieval needs of both legal professionals and laymen.

A variety of legal documents are increasingly being made available in electronic format. Automatic Information Search and Retrieval algorithms play a key role in enabling efficient access to such digitized documents. Although keyword-based search is the traditional method used for text retrieval, they perform poorly when literal term matching is done for query processing, due to synonymy and ambivalence of words. To overcome these drawbacks, an ontological framework to enhance the user’s query for retrieval of truly relevant legal judgments has been proposed in this paper. Ontologies ensure efficient retrieval by enabling inferences based on domain knowledge, which is gathered during the construction of the knowledge base. Empirical results demonstrate that ontology-based searches generate significantly better results than traditional search methods.

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.

Experiments on memory-retrieval dynamics support the hypothesis that different mechanisms mediate processes of familiarity and recall (recollection). The minimal retrieval time for accurate recognition and frequency judgments is about 100 msec earlier than the minimal time to judge details such as modality or location. The difference is consistent with neurophysiological evidence. Retrieval dynamics data are also relevant to other aspects of Aggleton & Brown's target article.