A massive volume of unstructured data in the form of comments, opinions, and other sorts of data is generated in real-time with the growth of web 2.0. Due to the unstructured nature of the data, ...building an accurate predictive model for sentiment analysis remains a challenging task. While various DNN architectures have been applied to sentiment analysis with encouraging results, they suffer from high dimensional feature space and consider various features equally. State-of-the-art methods cannot properly leverage semantic and sentiment knowledge to extract meaningful relevant contextual sentiment features.This paper proposes a sentiment and context-aware hybrid DNN model with an attention mechanism that {intelligently learns and highlights salient features of relevant sentiment context in the text. We first use integrated wide coverage sentiment lexicons to identify text sentiment features then leverage bidirectional encoder representation from transformers to produce sentiment-enhanced word embeddings for text semantic extraction. After that, the proposed approach adapts the BiLSTM to capture both word order/contextual text semantic information and the long-dependency relation in the word sequence. Our model also employs an attention mechanism to assign weight to features and give greater significance to salient features in the word sequence. Finally, CNN is utilized to reduce the dimensionality of feature space and extract the local key features for sentiment analysis. The effectiveness of the proposed model is evaluated on real-world benchmark datasets demonstrating that the proposed model significantly improves the accuracy of existing text sentiment classification.
The paper focuses on a short text copied in the thirteenth-century manuscript Ricc. 217, preserved in Biblioteca Riccardiana (Florence), known by the title
Fragmentum disputationis de Alcorani ...eloquentia inter Muslimum et Christianum
. It is a brief Christian polemical argumentation over the eloquence of the Qur’anic language and the Islamic dogma of the inimitability of the Qur’an (
iʿjāz
) in which the Dominican missionary Ramon Martì is named. Some historical, linguistic, codicological, and philological aspects will be taken into account to contribute to the discussion related to the possible genesis of this text, and the authorship of the
Vocabulista in Arabico
, the famous Arabic – Latin/Mozarabic lexicon preserved in the same codex. The short text of the
Fragmentum
is examined with a particular focus on its Qur’anic quotations, which are put in relation with other echoes of the similar disputes between Christians and Muslims and reported in different sources.
Semantic action recognition aims to classify actions based on the associated semantics, which can be applied in video captioning and human‐machine interaction. In this paper the problem is addressed ...by jointly learning multiple pose lexicons based on multiple body parts. Specifically, multiple visual pose models are learnt, and one visual pose model is associated with one body part, which characterises the likelihood of an observed video frame being generated from hidden visual poses. Moreover, multiple pose lexicon models are simultaneously learnt along with visual pose models. One pose lexicon model is associated with one body part that establishes a probabilistic mapping between the hidden visual poses and semantic poses parsed from textual instructions. To capture the temporal relations among body parts, a transition model is also learnt to measure the probability of the alignment transitioned from one position to another position. The body part‐based pose lexicon learning provides a novel method of cross‐modality semantic correlation, which can be applied in other spatial and temporal data. Action classification is finally formulated as the problem of finding the maximum posterior probability that a given multiple sequences of visual frames follow multiple sequences of semantic poses, subject to the most likely visual pose sequences and alignment sequences. Experiments were conducted on five action datasets to validate the effectiveness of the proposed method.
Soil invertebrates are assumed to play a major role in ecosystem dynamics, since they are involved in soil functioning. Functional traits represent one of the main opportunities to bring new insights ...into the understanding of soil invertebrate responses to environmental changes. They are properties of individuals which govern their responses to their environment. As no clear conceptual overview of soil invertebrate trait definitions is available, we first stress that previously-described concepts of trait are applicable to soil invertebrate ecology after minor modification, as for instance the inclusion of behavioural traits. A decade of literature on the use of traits for assessing the effects of the environment on soil invertebrates is then reviewed. Trait-based approaches may improve the understanding of soil invertebrate responses to environmental changes as they help to establish relationships between environmental changes and soil invertebrates. Very many of the articles are dedicated to the effect of one kind of stress at limited spatial scales. Underlying mechanisms of assembly rules were sometimes assessed. The patterns described seemed to be similar to those described for other research fields (e.g. plants). The literature suggests that trait-based approaches have not been reliable over eco-regions. Nevertheless, current work gives some insights into which traits might be more useful than others to respond to a particular kind of environmental change. This paper also highlights methodological advantages and drawbacks. First, trait-based approaches provide complementary information to taxonomic ones. However the literature does not allow us to differentiate between trait-based approaches and the use of a priori functional groups. It also reveals methodological shortcomings. For instance, the ambiguity of the trait names can impede data gathering, or the use of traits at a species level, which can hinder scientific interpretation as intra-specific variability is not taken into account and may lead to some biases. To overcome these shortcomings, the last part aims at proposing some solutions and prospects. It concerns notably the development of a trait database and a thesaurus to improve data management.
Man nimmt an, dass wirbellose Bodentiere eine wichtige Rolle bei der Ökosystemdynamik spielen, da sie am Funktionieren der Böden beteiligt sind. Funktionelle Merkmale bilden eine der wichtigsten Möglichkeiten für ein neues Verständnis der Reaktion von Bodenwirbellosen auf Umweltänderungen. Es handelt sich um Eigenschaften von Individuen, die deren Reaktion auf die Umwelt bestimmen. Da es keinen klaren konzeptionellen Überblick über die Merkmalsdefinitionen für Bodenwirbellose gibt, betonen wir zunächst, dass existierende Konzepte nach geringen Modifikationen auf die Ökologie von Bodenwirbellosen anwendbar sind, wie z.B. das Einbeziehen von Verhaltensmerkmalen. Anschließend betrachten wir ein Jahrzehnt der Literatur zum Gebrauch von Merkmalen bei der Abschätzung der Effekte der Umwelt auf Bodenwirbellose. Merkmalsbasierte Ansätze können unser Verständnis der Reaktionen von Bodenwirbellosen auf Umweltänderungen verbessern, da sie helfen, Beziehungen zwischen Umweltänderungen und Bodenwirbellosen zu etablieren. Sehr viele der Artikel widmen sich dem Effekt eines Stressfaktors auf begrenzten räumlichen Skalen. Die zugrundeliegenden Mechanismen von Vergemeinschaftungsregeln wurden manchmal bestimmt. Die beschriebenen Muster scheinen denen von anderen Forschungsgebieten (z.B. Pflanzen) ähnlich zu sein. Die Literatur legt nahe, dass merkmalsbasierte Ansätze über Ökoregionen hinweg nicht zuverlässig sind. Nichtsdestotrotz lassen aktuelle Arbeiten erkennen, welche Merkmale nützlicher als andere sein könnten, um auf spezielle Umweltveränderungen zu reagieren. Diese Arbeit stellt auch methodische Vor- und Nachteile heraus. Zuerst liefern merkmalsbasierte Ansätze Informationen, die taxonomische ergänzen. Indessen erlaubt uns die Literatur nicht, zwischen merkmalsbasierten Ansätzen und dem Gebrauch von a-priori definierten funktionellen Gruppen zu unterscheiden. Sie zeigt auch methodische Unzulänglichkeiten. So kann z.B. die Mehrdeutigkeit von Merkmalsbezeichungen das Sammeln von Daten behindern, oder der Gebrauch von Merkmalen auf der Artebene, der die wissenschaftliche Interpretation erschweren kann, da die intraspezifische Variabilität nicht berücksichtigt wird und zu gewissen Verzerrungen führen kann. Um diese Unzulänglichkeiten zu überwinden, hat der letzte Teil zum Ziel, einige Lösungen und Ausblicke vorzuschlagen. Dies betrifft namentlich die Entwicklung einer Merkmalsdatenbank und eines Thesaurus’ um die Datenverwaltung zu verbessern.
Sentiment analysis (SA) is a rapidly evolving field that aims at computationally categorizing the opinions of people about a particular product, movie, brand or anything that can be opined. It has ...changed the way the information is perceived and utilized by big business groups, brands and marketing agencies by demonstrating that the computational recognition of a sentimental expression is feasible. The fruition of Internet based applications has generated huge amount of personalized views on the Web. These reviews exist in different forms like social Medias, blogs, Wiki or forum websites. The boom of search engines like Yahoo and Google has flooded users with copious amount of relevant reviews about specific destinations, which is still beyond human comprehension. Sentiment Analysis poses as a powerful tool for users to extract the needful information, as well as to aggregate the collective sentiments of the reviews. This research will explore and compare the various techniques used for Sentiment Analysis in the last decade.
Roman Urdu and English are often used together as a hybrid language for communication on social media. Because writers don't worry about spelling when utilizing the English alphabet to write Urdu ...during texting, it becomes challenging to interpret mixed codes for emotions. There are over 14,000 emotion lexicons in this dataset, each of which lists nine different emotions and their polarities. The NRC emotion lexicons 8 provided in Urdu have been transliterated into Roman Urdu. To verify that the provided translation is accurate, we used three online dictionaries of Urdu. A Python script that transliterates words from Urdu to Roman Urdu has been used to develop Roman Urdu transliteration. Sentiment and mood, depending on the emotion lexicon, are also provided. The textual data has been annotated using the unigram feature and distance estimation among strings and lexicons. Approximately 10,000 sentences from the baseline sample have been automatically annotated.
Consumers are becoming increasingly aware of the health benefits of dairy ingredients. However, products fortified with dairy proteins are experiencing considerable aroma challenges. Practices to ...improve the flavor quality of dairy proteins require a comprehensive understanding of the nature and origins of off-aroma. Unfortunately, existing information from the literature is fragmentary. This review presents sensory lexicons and chemical structures of off-aromas from major dairy ingredients, and it explores their possible precursors and formation mechanisms. It was found that similar chemical structures often contributed to similar off-aroma descriptors. Lipid degradation and Maillard reaction are two primary pathways that commonly cause aroma dissatisfaction. Traditional and novel flavor chemistry tools are usually adopted for off-aroma measurements in dairy ingredients. Strategies for improving aroma quality in dairy derived products include carefully selecting starting materials for formulations, and actively monitoring and optimizing processing and storage conditions.
Language identification (LI) in textual documents is the process of automatically detecting the language contained in a document based on its content. The present language identification techniques ...presume that a document contains text in one of the fixed set of languages. However, this presumption is incorrect when dealing with multilingual document which includes content in more than one possible language. Due to the unavailability of standard corpora for Hindi-English mixed lingual language processing tasks, we propose the language lexicons, a novel kind of lexical database that augments several bilingual language processing tasks. These lexicons are built by learning classifiers over English and transliterated Hindi vocabulary. The designed lexicons possess condensed quantitative characteristics which reflect their linguistic strength in respect of Hindi and English language. On evaluating the lexicons, it is observed that words of the same language tend to cluster together and are separable over language classes. On comparing the classifier performance with existing works, the proposed lexicon models exhibit the better performance.
Ontologies are frequently used in information retrieval being their main applications the expansion of queries, semantic indexing of documents and the organization of search results. Ontologies ...provide lexical items, allow conceptual normalization and provide different types of relations. However, the optimization of an ontology to perform information retrieval tasks is still unclear. In this paper, we use an ontology query model to analyze the usefulness of ontologies in effectively performing document searches. Moreover, we propose an algorithm to refine ontologies for information retrieval tasks with preliminary positive results.
Verb classes are defined in lexical-semantics literature as syntactically coherent groups of verbs that also share meaning components. Thus, the investigation of verb classes leads to important ...insights into the syntax-semantics interface. In this perspective, starting from Levin’s (1993) foundational work for English, many authors have developed analyses for the syntactic-semantic classification of verbs in different languages. The aim of this paper is to provide an overview of such studies, focusing on those that constitute online open access resources for the syntactic-semantic classification of verbs: VerbNet for English, BVI for Basque, AnCoraVerb for Spanish and Catalan, VerboWeb for Brazilian Portuguese, CROVALLEX for Croatian, and VALLEX for Czech. Thus, this paper reviews the general theoretical assumptions on verb classification shared by all the works presented, and shows the specific characteristics of each one, considering the body of data, the specific theoretical perspective, analyses and methodology, and the search engines they provide. Finally, it offers a comparative analysis of two specific verb classes (namely, image creation verbs and verbs of creation and transformation), drawing on data from the studies mentioned above. Although these resources assume a specific lexical-semantic approach for verb classification, they provide valuable data and analyses that can be useful for research in different theoretical perspectives.
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