Considered as a rich source of information, social networking sites have been created lot of buzz because people share and discuss their opinions freely. Sentiment analysis is used for knowing voice or response of cro...
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ISBN:
(纸本)9789897581069
Considered as a rich source of information, social networking sites have been created lot of buzz because people share and discuss their opinions freely. Sentiment analysis is used for knowing voice or response of crowd for products, services, organizations, individuals, events, etc. Due to their importance, people opinions are analyzed in several domains including information retrieval, semantic web, text mining. These researches define new classification techniques to assign positive or negative opinion. Decisional systems like WeBhouse, known by their data-consuming must be enriched by this kind of pertinent opinions to give better help to decision makers. Nevertheless, cleaning and transformation processes recognized by several approaches as a key of WeBhouse development, don't deal with sentiment analysis. To fulfill this gap, we propose a new analysis algorithm which determines user's sentiment score of a post shared on the social network Facebook. This algorithm analyzes user's opinion depending on opinion terms and emoticons included in his comments. This algorithm is integrated in transformation process of ETL approach.
Explicit knowledge extracted from data, formalized tacit knowledge from experts or even knowledge existing in business sources may be in several heterogeneous formal representations and structures: as rules, models, f...
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ISBN:
(纸本)9789897580970
Explicit knowledge extracted from data, formalized tacit knowledge from experts or even knowledge existing in business sources may be in several heterogeneous formal representations and structures: as rules, models, functions, etc. However, a knowledge warehouse should solve this structural heterogeneity before storing knowledge. This requires specific tasks of harmonizing. This paper first presents our proposed definition and architecture of a knowledge warehouse, and then presents some languages for knowledge representations as particular the MOT (Modeling with Object Types) language. In addition, we suggest a metamodel for the MOT, and a metamodel for the explicit knowledge obtained using decision trees technique. As we aim to represent knowledge having different modeling formalisms into MOT, as a unified model, then we suggest a set of transformation rules that assure the move from the decision tree source model into the MOT target model. This work is still in progress, it is currently completed with tranformations for additional.
Transducers namely transducer cascades are used in several NLP-applications such as Arabic named entity recognition (ANER). To experiment and evaluate an ANER process, a weight coverage corpus is necessary. In this pa...
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Transducers namely transducer cascades are used in several NLP-applications such as Arabic named entity recognition (ANER). To experiment and evaluate an ANER process, a weight coverage corpus is necessary. In this paper, we propose an ANER method based on transducer cascade. The proposed transducer cascade is generated with the CasSys tool integrated in Unitex linguistic platform. The experimentation of our method is done on a Wikipedia corpus. The Wikipedia text format is obtained with Kiwix tool. The experiment results are satisfactory based on calculated measures.
Semantic relatedness between terms plays an important role in many applications, such as information retrieval, in order to disambiguate document content. This latter is generally studied among pairs of terms and is u...
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ISBN:
(纸本)9789897580246
Semantic relatedness between terms plays an important role in many applications, such as information retrieval, in order to disambiguate document content. This latter is generally studied among pairs of terms and is usually presented in a non-linear way. This paper presents a new statistical method for detecting relationships between terms called Least Square Mehod which defines these relations linear and between a set of terms. The evaluation of the proposed method has led to optimal results with low error rate and meaningful relationships. Experimental results show that the use of these relationships in query expansion process improves the retrieval results.
Upgrades to advanced scientific user facilities such as next-generation x-ray light sources,nanoscience centers,and neutron facilities are revolutionizing our understanding of materials across the spectrum of the phys...
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Upgrades to advanced scientific user facilities such as next-generation x-ray light sources,nanoscience centers,and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences,from life sciences to ***,these facility and instrument upgrades come with a significant increase in *** by more exacting scientific needs,instruments and experiments become more intricate each *** increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced *** language models(LLMs)can perform complex information retrieval,assist in knowledge-intensive tasks across applications,and provide guidance on tool *** x-ray light sources,leadership computing,and nanoscience centers as representative examples,we describe preliminary experiments with a Context-Aware Language Model for Science(CALMS)to assist scientists with instrument operations and complex *** the ability to retrieve relevant information from facility documentation,CALMS can answer simple questions on scientific capabilities and other operational *** the ability to interface with software tools and experimental hardware,CALMS can conversationally operate scientific *** making information more accessible and acting on user needs,LLMs could expand and diversify scientific facilities’users and accelerate scientific output.
Arabic named entities (ANE) are often sources of information. That is why they are used by several applications of natural language processing (NLP) mainly in information retrieval. In order to improve the relevance o...
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Over the last few years there has been a phenomenal growth in the use of WWW (World Wide Web) for a wide variety of purposes from advertising and publicity, to collaborative work and teaching. Because it is so easy to...
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In this paper, we propose a new approach to identify programs in TV streams. In the first step of our approach, we construct a reference catalogue for video grammars of visual jingles. In the second step, we identify ...
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ISBN:
(纸本)9781605586595
In this paper, we propose a new approach to identify programs in TV streams. In the first step of our approach, we construct a reference catalogue for video grammars of visual jingles. In the second step, we identify programs in TV streams by examining the similarity of the video signal to the visual grammars in the catalogue. After presenting our approach, we report the results of its experimental evaluation on several streams extracted from different channels and composed of several programs. Copyright 2009 ACM.
The task of assessing, grouping and arranging data into meaningful groups or clusters based on their similarities/dissimilarities measures known as cluster analysis. Thereby, there are numerous clustering algorithms: ...
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The sentiment classification is one of the new challenges emerged with the advence of social networks. Our purpose is to determine the sentimental orientation of a Facebook comment (positive or negative) by using the ...
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The sentiment classification is one of the new challenges emerged with the advence of social networks. Our purpose is to determine the sentimental orientation of a Facebook comment (positive or negative) by using the linguistic approach. In most of the sentiment analysis applications using this approach, the sentiment lexicon plays a key role. Thus, it is very important to create a lexicon covering several sentiment words. For this reason, we address in this paper the problem how to group and list words present in the corpus into two dictionaries. We proposed a new automatic technique to create the positive and negative dictionaries that exploits the emotions symbols (emoticons, acronyms and exclamation words) present in comments. More importantly, our idea allows to enlarge these dictionaries with an enrichment step. Finally, by using these prepared dictionaries, we predict the positive and negative polarities of the comment. We evaluate our approach by comparison to human classification. Our results are also effective and consistent.
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