Search results for "natural language processing"
showing 10 items of 413 documents
Event-related potential indicators of text integration across sentence boundaries.
2007
An event-related potentials (ERPs) study examined word-to-text integration processes across sentence boundaries. In a two-sentence passage, the accessibility of a referent for the first content word of the second sentence (the target word) was varied by the wording of the first sentence in one of the following ways: lexically (explicitly using a form of the target word); conceptually (using a paraphrase of the target word), and situationally (encouraging an inference concerning the referent of the target word). A baseline condition had no coreference between the two sentences. ERP results on the target word indicated multiple effects related to word identification and word-to-referent mappi…
The formation of structurally relevant units in artificial grammar learning
2002
A total of 78 adult participants were asked to read a sample of strings generated by a finite state grammar and, immediately after reading each string, to mark the natural segmentation positions with a slash bar. They repeated the same task after a phase of familiarization with the material, which consisted, depending on the group involved, of learning items by rote, performing a short term matching task, or searching for the rules of the grammar. Participants formed the same number of cognitive units before and after the training phase, thus indicating that they did not tend to form increasingly large units. However, the number of different units reliably decreased, whatever the task that…
Neural Correlates of Visual versus Abstract Letter Processing in Roman and Arabic Scripts
2013
In alphabetic orthographies, letter identification is a critical process during the recognition of visually presented words. In the present experiment, we examined whether and when visual form influences letter processing in two very distinct alphabets (Roman and Arabic). Disentangling visual versus abstract letter representations was possible because letters in the Roman alphabet may look visually similar/dissimilar in lowercase and uppercase forms (e.g., c-C vs. r-R) and letters in the Arabic alphabet may look visually similar/dissimilar, depending on their position within a word (e.g., [Formula: see text] - [Formula: see text] vs. [Formula: see text] - [Formula: see text]). We employed a…
Normative data on the familiarity and difficulty of 196 Spanish word fragments
2005
In this article, normative data on the familiarity and difficulty of 196 single-solution Spanish word fragments are presented. The database includes the following indices: difficulty, familiarity, frequency, number of meanings, number of letters given in the fragment, first and/or last letters given, and ratio of letters to blanks. A factor analysis was performed on difficulty, and two factors were obtained. Frequency, familiarity, and number of meanings loaded highly on the first factor, which we consider to measure lexical processes, whereas number of letters in the fragment, first and/or last letters given, and ratio of letters to blanks loaded highly on the second factor, which we judge…
A Graph-Grammar Approach to Represent Causal, Temporal and Other Contexts in an Oncological Patient Record
1996
AbstractThe data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-specific heuristics. The knowledge of data contexts supports the retrospective understanding of the medical decision-making process and is a valuable base for further treatment. Conventional data models usually neglect the problem of context knowledge, or simply use free text which is not processed by the program. In connection with the development of the knowledge-based system THEMPO (The…
E-Hitz: A word frequency list and a program for deriving psycholinguistic statistics in an agglutinative language (Basque)
2007
We describe a Windows program that enables users to obtain a broad range of statistics concerning the properties of word and nonword stimuli in an agglutinative language (Basque), including measures of word frequency (at the whole-word and lemma levels), bigram and biphone frequency, orthographic similarity, orthographic and phonological structure, and syllable-based measures. It is designed for use by researchers in psycholinguistics, particularly those concerned with recognition of isolated words and morphology. In addition to providing standard orthographic and phonological neighborhood measures, the program can be used to obtain information about other forms of orthographic similarity, …
Knowledge Acquisition in Conceptual Ontological Artificial Intelligence System
2009
The paper deals with active knowledge acquisition based on dialogue between AI system and its user. Presented method uses Conceptual Ontological Object Orientated System (COOS) to distinguish differences between concepts and to unequivocally process the input stream. In case of concepts, that do not exist in the system yet, adequate algorithms are being used to position them in ontological core. Separate concepts differ in attributes values or in sets of direct connections with other concepts. The communication aspect of the system deliver information that allow generating proper interpretation for userpsilas statement.
DeepEva: A deep neural network architecture for assessing sentence complexity in Italian and English languages
2021
Abstract Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (e.g., lexical, syntactical, morphological) to measure the grade of comprehensibility of a text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it can support the research on Automatic Text Simplification (ATS), a research area that deals with the study of new methods for transforming a text by changing its lexicon and structure to meet specific reader needs. In this paper, we illustrate an ATE approach named De…
Using Tsetlin Machine to discover interpretable rules in natural language processing applications
2021
Tsetlin Machines (TM) use finite state machines for learning and propositional logic to represent patterns. The resulting pattern recognition approach captures information in the form of conjunctive clauses, thus facilitating human interpretation. In this work, we propose a TM-based approach to three common natural language processing (NLP) tasks, namely, sentiment analysis, semantic relation categorization and identifying entities in multi-turn dialogues. By performing frequent itemset mining on the TM-produced patterns, we show that we can obtain a global and a local interpretation of the learning, one that mimics existing rule-sets or lexicons. Further, we also establish that our TM base…
Combining a context aware neural network with a denoising autoencoder for measuring string similarities
2020
Abstract Measuring similarities between strings is central for many established and fast-growing research areas, including information retrieval, biology, and natural-language processing. The traditional approach to string similarity measurements is to define a metric with respect to a word space that quantifies and sums up the differences between characters in two strings; surprisingly, these metrics have not evolved a great deal over the past few decades. Indeed, the majority of them are still based on making a simple comparison between character and character distributions without considering the words context. This paper proposes a string metric that encompasses similarities between str…