Preferred Semantics Research Articles

Enhancing Knowledge of Propagation-Perception-Based Attention Recommender Systems

Researchers have introduced side information such as social networks or knowledge graphs to alleviate the problems of data sparsity and cold starts in recommendation systems. However, most of the methods ignore the exploration of feature differentiation aspects in the knowledge propagation process. To solve the above problem, we propose a new attention recommendation method based on an enhanced knowledge propagation perception. Specifically, to capture user preferences in a fine-grained manner in a knowledge graph, an asymmetric semantic attention mechanism is adopted. It identifies the influence of propagation neighbors on user preferences through a more precise representation of the preference semantics for head and tail entities. Furthermore, in consideration of the memory and generalization of different propagation depth features and adaptively adjusting the propagation weights, a new propagation feature exploration framework is designed. The performance of the proposed model is validated by two real-world datasets. The baseline model averagely increases by 9.65% and 9.15% for the Area Under Curve (AUC) and Accuracy (ACC) indicators, which proves the effectiveness of the model.

Corpus Linguistic Methodology as an Advanced Conversion Design for Social Science Research

This article offers a corpus linguistics methodology (i.e., guiding the collection of language-based qualitative data, queried with both qualitative and quantitative methods, and mixed analytical approaches) as a unique and practical advance in the conversion mixed methods design. The conversion mixed methods design takes qualitative or quantitative data, and reforms, queries, or analyzes that data using a converse qualitative, quantitative, or mixed method. I argue that the design is uniquely suited to maximize the interlinking of language-based data within strands, as well as in cross-strand comparison. The article focuses on several concepts in corpus linguistics, specifically collocation (i.e., multiple words appearing together), semantic preference (i.e., the tendency of those words to appear in certain contexts), and semantic prosody (i.e., the sociocultural meaning of those words in that context), and covers both conceptual background and procedures for carrying out analyses. Further, the approach demonstrates the utility of more fluid design description by focusing on the timing and purpose of integration. I articulate this argument by outlining a study on the opioid epidemic in elderly health services in rural Pennsylvania, with the help of a zipper metaphor to describe the design. The article concludes with a discussion of the value of this advanced design to mixed methods researchers representing the social sciences outside of linguistics-centered disciplines, at a methodological level, as well as the ready availability of tools that allow researchers to instrumentalize the design.

SEMANTIC PROSODY AND PREFERENCE OF “HEALTHY” AND “UNHEALTHY” COLLOCATIONS IN COVID-19 CORPUS

This study is conducted in order to know the collocations of ‘healthy’ and ‘unhealthy’ as well as to explore the lexical meaning of those collocations. Corpus-based approach is employed in this study since the sole source of the data is the corpus data. Qualitative research method is used in order to find the hypotheses from the corpus data which is taken from Sketch Engine. The results demonstrate that the collocations of two node words are dissimilar in the categorization. ‘healthy’ node word indicates that three major semantic preferences are associated with it - human, animal, disease. On the contrary, the semantic preferences of ‘unhealthy’ node word are diverse. Thus, the classification is based on the meaning of the collocations. The collocations with negative meaning occur more frequently than those with positive meaning. It is due to the fact that they use the prefixes –in and –un which create the opposite meaning of the original word. Therefore, the negative semantic prosody is more frequently found the two node words – ‘healthy’ and ‘unhealthy’.

The affect bias in the metaphorical representation of anticipated events

Abstract When talking about anticipated events, speakers can conceptualize them either as destinations towards which they are moving or as entities moving towards them, which correspond to the Ego- and the Time-moving metaphors, respectively (cf. ‘We are approaching Christmas’ and ‘Christmas is approaching’). Research in psycholinguistics has shown affective valence, i.e. whether the conceptualized event is perceived as positive or negative, to be one of the factors that modulate metaphor choice; positive anticipation is preferentially associated with Ego-moving expressions, whereas negative anticipation is predominantly associated with Time-moving metaphors. This paper sets out to test if the time-affect association surfaces in naturally-occurring language use when both metaphorical patterns are available. By focusing on the temporal usage of the verb approach, we provide linguistic evidence in favor of such an affective bias in time representations. In addition, the language data point to a semantic preference for a particular type of event (i.e., personal vs social) under each metaphorical pattern. We interpret this finding as preliminary evidence for a possible semantic bias in time representations to be further investigated.

Náisiúin Gaelach: Questions of Identity and Nationalism in the Irish Language

The current paper investigates the construction of nationhood in the Irish language through the use of a Corpus Assisted Discourse Analysis (CADA) looking at terms coding identity in the Irish language. Using the New Corpus for Ireland the terms Gael, Gaelach and Éireannach were analysed for frequency of occurrence, semantic prosody and semantic preference in the corpus. Furthermore a collocation analysis of each of the terms was carried out. Through the use of these analytical techniques insight was gathered into the contextual usage of these terms. These insights were analysed through the prism of Kolakowski’s (1995) criteria for the establishment of a nation in order to ascertain whether the usage of these terms reflected the conceptualisation of speakers’ nationhood in terms of a separate and unique national identity. Findings showed evidence of a distinct national spirit, historical memory and a national body among Irish-language speakers, three of Kolakowski’s criteria. While evidence surrounding Kolakowski’s other criteria of a nameable beginning and an orientation to, and consciousness of, the future may be drawn from the findings, ultimately more work is needed to more rigorously establish that these criteria have been met.

Застосування корпусних технологій у навчанні галузевого перекладу

Corpus technologies (corpora of English and Ukrainian texts and tools for their processing) represent modern specialized discourse and facilitate searching for and comparing different units of translation, which makes them a useful tool for both practicing and trainee translators. The purpose of this article is to determine the role and place of corpus technologies in teaching specialized translation on the example of the oil and gas industry. Comparative and parallel text corpora are characterized. The paper reveals methods of applying mono- and bilingual comparative and parallel corpora and corpus managers for acquiring knowledge about genre-stylistic features of texts; developing skills to distinguish a term and determine its collocation profile and semantic preference; analyze translation techniques; translate collocations, complex noun constructions, verbal phrases, and abbreviations. Examples of relevant exercises and tasks that should be performed at the translation training stage are given. Further research should be aimed at integrating corpus-based tasks into the translation practice stage involving the implementation of a translation project.

Argument-related recurrent sequences: A corpus-based study targeting L2 learners of English

Legal sentencing involves a multilayered series of arguments leading to a final verdict, just as argumentative essays, a frequent task genre in language classes, should include multilayered argumentation leading to the writer’s conclusions. This similarity suggests that authentic legal sentencing discourse could potentially be useful for language pedagogy. Yet this specific written genre has not attracted much attention in EFL contexts. This study examines three corpora of legal sentencing data (i.e., verdicts of guilty, innocent, and partially innocent when the charges involve more than one crime), amounting to 650,000 words. The study identifies lexical bundles in each corpus and their semantic preferences (i.e., co-occurring words of the sequences in context) in concordance lines. The findings illuminate features of the sentencing genre and suggest its potential as a pedagogical tool for teaching argumentative prose to L2 English learners at the secondary and tertiary levels.

Harnessing Incremental Answer Set Solving for Reasoning in Assumption-Based Argumentation

AbstractAssumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for developing effective algorithms for reasoning tasks in the logic programming fragment of ABA that are presumably hard for the second level of the polynomial hierarchy, including skeptical reasoning under preferred semantics as well as preferential reasoning. In particular, we develop non-trivial counterexample-guided abstraction refinement procedures based on incremental ASP solving for these tasks. We also show empirically that the procedures are significantly more effective than previously proposed algorithms for the tasks.

Corpus-based cognitive semantics: Extended units of meaning and their implications for Translation Studies

Traditional lexical semantics focuses on the meaning of individual lexemes. Firth (1957) brought our attention to collocations and the fact that meaning is not isolated in the lexeme. In 1996 Sinclair argued for the existence of extended units of meaning which, as the expression indicates, go beyond the lexeme. In recent years Stubbs (2001b), and other corpus linguists have convincingly shown that meaning is a phraseological phenomenon to a high degree. Corpus searches allow us to study lexemes in their immediate context, study their most frequent collocates and thus help us reveal their semantic preferences (Sinclair 1987, 1996) and semantic prosodies (evaluation) (Louw 1993). Some of the findings confirm intuitions, whereas some make us aware of connotations which we have never before consciously known the existence of. In this article, I shall argue for the application of corpus-based cognitive semantics as a tool for researchers within translation studies (TS) who are particularly interested in revealing evaluative aspects of the units of meaning of source texts and their translations. What may formerly have been described as something intangible like an ‘atmosphere’, now becomes tangible because of the patterns emerging from large numbers of examples. I shall provide empirical examples in various langua ges of such evaluative patterns which are of course not automatically generated but come about as the result of computer-generated concordance lines and thorough manual analysis.

A Neural Network Model of Lexical-Semantic Competition During Spoken Word Recognition.

Visual world studies show that upon hearing a word in a target-absent visual context containing related and unrelated items, toddlers and adults briefly direct their gaze toward phonologically related items, before shifting toward semantically and visually related ones. We present a neural network model that processes dynamic unfolding phonological representations of words and maps them to static internal lexical, semantic, and visual representations. The model, trained on representations derived from real corpora, simulates this early phonological over semantic/visual preference. Our results support the hypothesis that incremental unfolding of a spoken word is in itself sufficient to account for the transient preference for phonological competitors over both unrelated and semantically and visually related ones. Phonological representations mapped dynamically in a bottom-up fashion to semantic-visual representations capture the early phonological preference effects reported in visual world tasks. The semantic visual preference typically observed later in such a task does not require top-down feedback from a semantic or visual system.

A methodology for Qur’anic lexical translation

Abstract The present study propounds a methodology for the translation of Qur’anic lexis in a way that synergizes semantic preference, discourse prosody, and para/intertextuality. Towards the validation of this methodology, the Qur’anic lexical item آيـة (āyah) is investigated at two levels: (a) the intertextual level of the semantic preferences emerging in the various co-texts of āyah inside the Qurʼan and (b) the paratextual level of the overall discourse prosody underlying these semantic preferences in the exegetical contexts of āyah. The research finds firstly that there are four semantic preferences associated with āyah, viz. cosmological phenomena, miraculous tokens, conclusive evidence, and divine revelations/communications. Second, the discourse prosody underlying the Qurʼanic usages of āyah is divine visibility, which motivates the word’s generic English translation as “sign.” Third, in rendering the lexical item آيـة (āyah) into English, the well-known Qur’an translators in the Qurʼanic Arabic Corpus have opted either for “sign,” to maintain the positive discourse prosody associated with the Qur’anic usages of the item, or “token,” “portent,” “miracle(s),” or “verse/revelations/communications,” with a view to observing the semantic preferences associated with them.

Exploring user historical semantic and sentiment preference for microblog sentiment classification

Microblog text is usually very short, thereby challenging existing sentiment classification methods by providing models with little context. Recently, historical user information has been widely used in many real-world applications, such as recommender systems. However, few research works consider user historical states in the loop of microblog sentiment analysis. In this work, we propose to involve historical user information for microblog sentiment analysis to alleviate the context sparsity problem. In particular, we propose a novel neural microblog sentiment classification method which learns informative representations of microblog posts by exploiting both a user’s contextual information and his/her historical state information. The proposed method consists of four components, i.e., a micropost encoder, a user historical sentiment encoder, a User Historical Semantic Encoder, and a micropost sentiment classification component. Extensive experiments are conducted on real-world data collected from Weibo, and experimental results show that the proposed approach achieves superior performance as compared to state-of-the-art baselines.

Syntactic and Semantic Influences on the Time Course of Relative Clause Processing: The Role of Language Dominance

We conducted a visual world eye-tracking experiment with highly proficient Spanish-English bilingual adults to investigate the effects of relative language dominance, operationalized as a continuous, multidimensional variable, on the time course of relative clause processing in the first-learned language, Spanish. We found that participants exhibited two distinct processing preferences: a semantically driven preference to assign agency to referents of lexically animate noun phrases and a syntactically driven preference to interpret relative clauses as subject-extracted. Spanish dominance was found to exert a distinct influence on each of these preferences, gradiently attenuating the semantic preference while gradiently exaggerating the syntactic preference. While these results might be attributable to particular properties of Spanish and English, they also suggest a possible generalization that greater dominance in a language increases reliance on language-specific syntactic processing strategies while correspondingly decreasing reliance on more domain-general semantic processing strategies.

THE COLLOCATION MEANING OF “VACCINE” ON SEMANTIC APPROACH: A CORPUS-BASED ANALYSIS

<p>Corpus semantics examines the words that are used in text and discourse using observations as evidence of meaning. This study aims to investigate the collocations of node <strong><em>‘vaccine’</em></strong> based on semantic preference and semantic prosody using the corpus-based approach since the source of data is the corpus data. The qualitative research method is used to find the hypotheses from the corpus data taken from sub-corpus in Covid-19 corpus using Sketch Engine software. This study demonstrates that the node word of ‘vaccine’ in the semantic preference was shown six words related to the Covid-19 corpus. Meanwhile, the category of semantic prosody was displayed four words negative in meaning, and there was two words displayed positive in meaning, the collocations with negative meaning which occur more frequently than positive meaning. Thus, the writer concluded that the author of a reputable journal explained the word ‘vaccine’ with a negative perspective in Covid-19.</p>

Child and Children in a Corpus of American Fiction: Contrasting Semantic Preferences and Their Experiential Motivations

Abstract This study investigates the nature of the semantic differences between collexemes of singular child and plural children in a corpus of American fiction. Collexemes in three specific syntactic slots are investigated: adjectives in the attributive position, nouns grammatically possessed by child’s and children’s, and present participial forms of verbs in the position immediately to the right of child/children. The approach relies on Distinctive Collexeme Analysis to establish statistically significant differences, revealing a surprising variety of semantic distinctions not usually acknowledged in discussions of the singularity vs. plurality of count nouns. Finally, an attempt is made to relate the key findings to broader cognitive and behavioural realities.

Predicting Open-Ended Decisions: Understanding the Differential Roles of Semantic Memory and Preference (1303)

Predicting Open-Ended Decisions: Understanding the Differential Roles of Semantic Memory and Preference (1303)

A Corpus-based Comparative Study of “get-passive” Semantic Prosody

Research on semantic prosody education is playing a vital role in the process of learning English.This research is based on the LOB corpus (Lancaster-Oslo/Bergen corpus) and the IWriteBaby corpus, the core library of the IWrite Chinese English Learner Corpus. Using AntConc 3.5.7, to compare the semantic preference of the collocation words of get in the two corpora that meet the get-passive structure. Aiming to compare the semantic prosody differences between Chinese English learners and native speakers when they use the structure “get-passive”. It mainly focuses on the analysis of neutral collocation terms that have a higher frequency of co-occurrence with get and a mutual information value (I value) which is greater than or equal to 3. The research results show that Chinese English learners tend to have neutral semantic prosody when using this structure, while native speakers tend to prefer negative semantic prosody.With the combination of semantic prosody and corpus method should be attached importance to improve the level of English education.

Seasonality of Back Pain in Italy: An Infodemiology Study.

Background: E-health tools have been used to assess the temporal variations of different health problems. The aim of our infodemiology study was to investigate the seasonal pattern of search volumes for back pain in Italy. Methods: In Italian, back pain is indicated by the medical word “lombalgia”. Using Google Trends, we selected the three search terms related to “lombalgia” with higher relative search volumes (RSV), (namely, “mal di schiena”, “dolore alla schiena” and “dolore lombare”), representing the semantic preferences of users when performing web queries for back pain in Italy. Wikipedia page view statistics were used to identify the number of visits to the page “lombalgia”. Strength and direction of secular trends were assessed using the Mann–Kendall test. Cosinor analysis was used to evaluate the potential seasonality of back pain-related RSV. Results: We found a significant upward secular trend from 2005 to 2020 for search terms “mal di schiena” (τ = 0.734, p < 0.0001), “dolore alla schiena” (τ = 0.713, p < 0.0001) and “dolore lombare” (τ = 0.628, p < 0.0001). Cosinor analysis on Google Trends RSV showed a significant seasonality for the terms “mal di schiena” (pcos < 0.001), “dolore alla schiena” (pcos < 0.0001), “dolore lombare” (pcos < 0.0001) and “lombalgia” (pcos = 0.017). Cosinor analysis performed on views for the page “lombalgia” in Wikipedia confirmed a significant seasonality (pcos < 0.0001). Both analyses demonstrated a peak of interest in winter months and decrease in spring/summer. Conclusions: Our infodemiology approach revealed significant seasonal fluctuations in search queries for back pain in Italy, with peaking volumes during the coldest months of the year.

The role of phrasal verbs in phraseology

The aim of this article is to supplement existing research on English phraseology and its use in literary works by exploring the behavioural patterns of phrasal verbs, which is a recognized challenge among English language learners. This article contrasts a number of phrasal verbs and highlights their active use among the language speakers. This work includes collocation of phrasal verbs, their semantic preference and sequence. Each idea is supported by a definition and fairly illustrated by examples

Incremental Skeptical Preferred Acceptance in Dynamic Argumentation Frameworks

In this article, we tackle the problem of efficiently recomputing the skeptical acceptance of dynamic argumentation frameworks under the well-known preferred semantics. We discuss an incremental algorithmic solution whose main idea is that of exploiting the initial knowledge (including the update to perform) in order to identify a potentially small portion of the argumentation framework. Such a portion is sufficient to compute the skeptical preferred acceptance of a goal argument w.r.t. the whole updated framework. We also discuss on how similar ideas extend to more general argumentation frameworks.