{ "item_title" : "Natural Language Processing and Information Systems", "item_author" : [" Chris Biemann", "Siegfried Handschuh", "André Freitas "], "item_description" : "Improving Supervised Classification Using Information Extraction.- Supervised Machine Learning Techniques to Detect TimeML Events in French and English.- In Defense of Word Embedding for Generic Text Representation.- Using Distributed Word Representations and mRMR Discriminant Analysis for Multilingual Text Summarization.- Combining Pattern-Based and Distributional Similarity for Graph-Based Noun Categorization.- Acquiring a Large Scale Polarity Lexicon Through Unsupervised Distributional Methods.- Query Refinement Using Conversational Context: A Method and an Evaluation Resource.- Applying Semantic Parsing to Question Answering Over Linked Data: Addressing the Lexical Gap.- Pragmatic Query Answering: Results from a Quantitative Evaluation.- What was the Query? Generating Queries for Document Sets with Applications in Cluster Labeling.- Using Context-Aware and Semantic Similarity Based Model to Enrich Ontology Concepts.- NADIA: A Simplified Approach Towards the Development of Natural Dialogue Systems.- How to Talk to a Cognitive Computer.- Comparing Recursive Autoencoder and Convolutional Network for Phrase-Level Sentiment Polarity Classification.- The Interplay of Language Processing, Reasoning and Decision-Making in Cognitive Computing.- Towards Benevolent Sales Assistants in Retailing Scenarios.- A Rule-Based Approach to Implicit Emotion Detection in Text.- Deciphering Review Comments: Identifying Suggestions, Appreciations and Complaints.- Associating Intent with Sentiment in Weblogs.- PSO-ASent: Feature Selection Using Particle Swarm Optimization for Aspect Based Sentiment Analysis.- Improving Spanish Polarity Classification Combining Different Linguistic Resources.- Tree-Structured Named Entities Extraction from Competing Speech Transcriptions.- Interactive Learning with TREE: Teachable Relation and Event Extraction System.- Identification and Ranking of Event-Specific Entity-Centric Informative Content from Twitter.- Automatic Classification and PLS-PM Modeling for Profiling Reputation of Corporate Entities on Twitter.- An Adaptable and Personalised E-Learning System Based on Free Web Resources.- A Controlled Natural Language for Business Intelligence Monitoring.- Text Summarization and Speech Synthesis for the Automated Generation of Personalized Audio Presentations.- Unsupervised Classification of Translated Texts.- A Language-Independent Method for Detection and Correction of Alignment Errors in Parallel Corpora.- High-Precision Person Name Extraction from Turkish Texts Using Wikipedia.- A Hybrid Approach for Extracting Arabic Persons' Names and Resolving Their Ambiguity from Twitter.- Extracting Relations from Unstructured Text Sources for Music Recommendation.- Simulating Misreading.- (German) Language Processing for Lucene.- Optimized Uyghur Segmentation for Statistical Machine Translation.- Management and Publishing of Multimedia Dictionary of the Czech Sign Language.- Detection of Modality with ITGETARUNS.- Gathering Knowledge for Question Answering Beyond Named Entities.- MaNER: A MedicAl Named Entity Recogniser.- Upper Bound for Cross-Lingual Concept Mapping with External Translation Resources.- Generating Logical Representations for Natural Language Requirements Using Syntactic Dependencies and Norm Analysis Patterns.- Random Indexing Revisited.- On Developing Extraction Rules for Mining Informal Scientific References from Altmetric Data Sources.- Lemonade: A Web Assistant for Creating and Debugging Ontology Lexica.- A Comparative Study on Twitter Sentiment Analysis: Which Features are Good?.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/31/919/580/3319195808_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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