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Research on sentiment analysis of financial texts 7

Research on sentiment analysis of financial texts

引用

7th IEEE international conference on Electronics information and Emergency Communication, ICEIEC 2017

作者： Fang, Bing Liang, Sheng Zou, Qian Huang, Wei College of Mathematics and Information Science University of Guiyang Guiyang Guizhou Province China School of Physical Electronics University of Electronic Science and Technology Chengdu Sichuan Province China

ISBN: (纸本)9781509030248

With the rapid development of Internet technology, online documents on the Internet have become an important source of information. In particular, web financial texts have become vital source of financial information. As a result of the large amount of financial information on the Internet, ordinary users are unable to easily filter out v 1 aluable financial information in a short time, and relying solely on human resources cannot maximize the abundant information resources. To meet the various search requirements of users;reduce the time for collecting, filtering, and processing information;and improve user search efficiency, this study aims to employ two new non-subject dimensions of financial texts, namely, genre and sentiment, according to financial information retrieval habits and the different demands of users. Financial texts are divided into genres on the basis of the characteristics of financial texts to produce various characteristic items and provide effective text feature representation. Support vector machine is adopted to classify financial texts according to genre. With regard to the sentient analysis of texts, a financial text attribute extraction algorithm based on the Apriori algorithm is proposed to extract textual attributes and construct a financial sentiment lexicon. A financial text sentiment analysis algorithm is designed on the basis of the calculation rules of sentiment intensity to analyze affective disposition and the sentiment intensity of texts. © 2017 IEEE.

关键词： Sentiment analysis

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Text Mining Approach for Product Quality Enhancement (Improving Product Quality through Machine Learning) 7

Text Mining Approach for Product Quality Enhancement (Improv...

引用

7th IEEE international Advance Computing conference (IACC)

作者： Rangu, Chandrasekhar Chatterjee, Shuvojit Valluru, Srinivasa Rao HCL Technol Ltd Hyderabad Andhra Prades India

ISBN: (纸本)9781509015603

Text mining, also referred to as text data mining, is the process of extracting interesting and non-trivial patterns or knowledge from text documents. It uses algorithms to transform free flow text (unstructured) into data that can be analyzed (structured) by applying Statistical, Machine Learning and Natural language processing (NLP) techniques. Text mining is an evolving technology that allows enterprises to understand their customers well, and help them in redefining customer needs. As e-commerce is becoming more and more established, the number of customer reviews and feedback that a product receives has grown rapidly over a period of time. For a popular asset, the number of review comments can be in thousands or even more. this makes it difficult for the manufacturer to read all of them to make an informed decision in improving product quality and support. Again it is difficult for the manufacturer to keep track and to manage all customer opinions. this article attempts to derive some meaningful information from asset reviews which will be used in enhancing asset features from engineering point of view and helps in improving the support quality and customer experience

关键词： Text mining Natural language processing (NLP) crawling Support Vector Machine (SVM) Associate Rule Mining (ARM) Term Frequency (TF) Document Term Matrix (DTM) Stemming Lemmatization

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Data Structuring for Launching web Services Triggered by Media Content 7th

Data Structuring for Launching Web Services Triggered by Med...

引用

7th Joint international Semantic technology conference (JIST)

作者： Urakawa, Makoto Fujisawa, Hiroshi NHK Japan Broadcasting Corp Setagaya Ku 1-10-11 Kinuta Tokyo Japan

ISBN: (纸本)9783319706825;9783319706818

there are some efforts to inspire the viewers to buy something or visit somewhere when they are viewing such objects or places on the TV programs or web sites. It is required to link some specific services, which can be run on smartphones or tablets, to content on TV or a web site. However, simple combination of content and possible services still requires some operations taken by the viewers such as typing search words in the applications or the pages of the services. Such required actions may decline their motivations to use the services. therefore, the authors propose the data model that allows to seek matching of an entity within content with various services, and to generate service launch information dynamically changed by combination of an entity and a service. the data model is based on combination of ontology class structure and reasoning. In this paper, effectiveness of the data model is shown by the prototype applications which call various web services to inspire viewers for subsequent actions in accordance with media content.

关键词： Ontology Resource description framework Knowledge base Linked data Semantic web rule language Inference Ifttt

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

引用

7th international conference on web Intelligence, Mining and Semantics, WIMS 2017

ISBN: (纸本)9781450352253

the proceedings contain 35 papers. the topics discussed include: towards easier visualization of linked data for lay users;large-scale storage and query processing for semantic sensor data;exploring lurking behaviors in online social networks;knowledge extraction from on-line open source bug tracking systems to predict bug-fixing time;a time series classification approach to game Bot detection;evolutionary mining of relaxed dependencies from big data collections;HERMEVENT: a news collection for emerging-event detection;querying and searching the deep web;on the SPARQL metamodeling semantics entailment regime for OWL 2 QL ontologies;semantic technology for open data publishing;efficient top-k shortest path query processing in sparse graph databases;mitigating linked data quality issues in knowledge-intense information extraction methods;analysis of semantic URLs to support automated linking of structured data on the web;managing road safety through the use of linked data and heat maps;an extended spreading activation technique for hashtag recommendation in microblogging platforms;a real-time twitter sentiment analysis using an unsupervised method;and an innovative majority voting mechanism in interactive social network clustering.

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Querying Deepweb Data Sources as Linked Data 17

Querying DeepWeb Data Sources as Linked Data

引用

7th international conference on web Intelligence, Mining and Semantics, WIMS 2017

作者： Anelli, Vito W. Bellini, Vito Calí, Andrea De Santis, Giuseppe Di Noia, Tommaso Di Sciascio, Eugenio SisInf Lab Politecnico di Bari Italy DCSIS Birkbeck Univ. of London and Oxford-Man Oxford Univ. United Kingdom

ISBN: (纸本)9781450352253

the Deep web is constituted by dynamically generated pages, usually requested through HTML forms;it is notoriously difficult to query and to search, as its pages are obviously non-indexable. Recently, Deep web data have been made accessible through RESTful services that return information usually structured in JSON or XML format. We propose techniques to make the Deep web available in the Linked Data Cloud, and we study algorithms for processing queries posed in a transparent way on the Linked Data, providing answers based on the underlying Deep web sources. We present a software prototype that exposes RESTful services as Linked Data datasets thus allowing a smoother semantic integration of different structured information sources in a global data and knowledge space. © 2017 ACM.

关键词： Linked data

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Biocarian: A search engine for performing exploratory searches of biological databases 11

Biocarian: A search engine for performing exploratory search...

引用

11th international conferences on Computer Graphics, Visualization, Computer Vision and Image processing, CGVCVIP 2017 and international conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2017

作者： Zaki, Nazar Tennakoon, Chandana College of Information Technology United Arab Emirates University Al Ain United Arab Emirates

ISBN: (纸本)9789898533661

there are a large number of web-based biological databases publicly available for scientists. In addition, many private databases are generated in the course of research projects. web standards have evolved in recent times, and semantic web technologies are now available to interconnect diverse and heterogeneous sources of data. therefore, the integration and querying of biological databases can be facilitated by semantic web techniques. the key idea is to describe data in the Resource Description Format (RDF) and to query them using the SPARQL language. In this paper, we introduce "BioCarian" an efficient and user-friendly search engine that can be used to perform exploratory searches of biological databases. the search engine acts as an interface for running SPARQL queries in RDF databases. In addition, we also provide a graphical interface based on facets that can be used to create advanced SPARQL queries. the facet interface is more advanced and novel than conventional facets. It allows complex queries to be constructed and includes additional features such as allowing facet values to be ranked based on several criteria, visually indicating the relevance of a facet value, and presenting the most important facet values when a large number of choices are available. We have constructed a prototype database that combines public databases that have gene-level, protein-level, and disease-level information. the search engine can be accessed from ***. © 2017.

关键词： Search engines

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7th international Workshop on Spoken Dialogue Systems, IWSDS 2016

引用

7th international Workshop on Spoken Dialogue Systems, IWSDS 2016

ISBN: (纸本)9789811025846

the proceedings contain 40 papers. the special focus in this conference is on the Northernmost Spoken Dialogue Workshop, Methods, Techniques for Spoken Dialogue Systems, Socio-Cognitive language processing, Towards Multilingual, Multimodal, Open Domain Spoken Dialogue Systems, Evaluation of Human-Robot Dialogue in Social Robotics, Dialogue Quality Assessment and Dialogue State Tracking Challenge 4. the topics include: DigiSami and digital natives;interaction technology for the north Sami language;a comparative study of text preprocessing techniques for natural language call routing;compact and interpretable dialogue state representation with genetic sparse distributed memory;incremental human-machine dialogue simulation;active learning for example-based dialog systems;question selection based on expected utility to acquire information through dialogue;a simple deep reinforcement learning dialogue system;breakdown detector for chat-oriented dialogue;user involvement in collaborative decision-making dialog systems;entropy-driven dialog for topic classification;detecting and tackling uncertainty;fisher kernels on phase-based features for speech emotion recognition;internationalisation and localisation of spoken dialogue systems;a multi-lingual evaluation of the vAssist spoken dialog system. Comparing disco and RavenClaw;an open-source modular web-based multimodal dialog framework;a framework to break the barrier across domains in spoken dialog systems;towards an open-domain social dialog system;extrinsic versus intrinsic evaluation of natural language generation for spoken dialogue systems and social robotics;engagement in dialogue with social robots;the negotiation dialogue game;convolutional neural networks for multi-topic dialog state tracking and dialogues with social robots.

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A Novel Gamification Approach to Recomendation Based Mobile Applications 9

A Novel Gamification Approach to Recomendation Based Mobile ...

引用

9th international conference on advanced Computing, ICoAC 2017

作者： Neeraj, S. Oswald, C. Sivaselvan, B. Department of Computer Engineering Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai India

ISBN: (纸本)9781538643495

Sites in E-Commerce tag like Amazon are now an integral section of the internet economy these days. Rapid growth in the smart phone market has excelled these sectors into the mainstream. there are many applications of recommender based system that is used by smartphone users such as e-commerce apps, travel apps and many others. the focus of this paper is to design an approach via data mining, human psychology techniques in interaction to make a mobile application profitable by making a large share of users tend to use the application for some significant time more and hence increase the company's revenue via advertisements or other means. this paper also focuses on increasing the usability to all the users of recommender based mobile applications and also on increasing the profit of the company. Integration of human computer interaction psychology and data mining with Natural language processing techniques helps in achieving the goal. Focus is made in generation of recommended results and its eventual generation of "wh" questions like who/what/when from the recommended object's property. A web scrapper is implemented to automatically fetch the recommended item's information from the web. Questions are generated as a set and ranked within the set. the question having the highest rank among all is then picked and linked to the notifications of the application at regular intervals. this notification linkage is done in accordance with the exploitation of the human mind's tendency of attention due to curiosity. Survey performed to find the improvement in the hit rate of the application and show the evidence and support of the motive. © 2017 IEEE.

关键词： Data mining

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Emerging Ideas on information Filtering and Retrieval: DART 2013 Revised and Invited Papers

引用

2017年

作者： Cristian Lai Alessandro Giuliani Giovanni Semeraro

ISBN: (纸本)9783319683904

this book addresses new challenges and emerging ideas in Distributed information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th international Workshop on information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII international conference of the Italian Association for Artificial Intelligence. the main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. the papers presented here offer a comprehensive review of related work and state-of-the-art techniques. the authors a mix of respected practitioners and researchers share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the books overall quality.

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Named Entity Identification Based Translation Disambiguation Model 7th

Named Entity Identification Based Translation Disambiguation...

引用

7th international conference on Pattern Recognition and Machine Intelligence (PReMI)

作者： Sharma, Vijay Kumar Mittal, Namita Malaviya Natl Inst Technol Jaipur Jaipur Rajasthan India

ISBN: (纸本)9783319699004;9783319698991

Machine Translation (MT) systems are in growing state for Indian languages, where either a translation or transliteration mechanism is used for a word or phrase. Identifying whether a word needs translation or transliteration mechanism, is still a challenge. Since the Named Entity (NE) terms have a property of similar pronunciation across the languages. So the Named Entity Identification (NEI) will be very useful for disambiguating the word in favor of either translation or transliteration. Term Frequency Model (TFM), i.e., a Cross-Lingual information Retrieval (CLIR) model is used to evaluate the NEI based translation disambiguation model.

关键词： Natural language processing systems

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