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Information and Knowledge Engineering

Management + Knowledge Acquisition Databases, Information Retrieval and Search Decision Support Systems Mining of Data Rich Sources Data and;

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Textual Information Access

retrieval; - text classification and clustering; - opinion mining; - comprehension aids (automatic summarization, machine translation;

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Advances in Distributed Agent-Based Retrieval Tools

) new challenges in search technology, (iii) sentiment analysis and opinion mining, (iv) distributed information retrieval, (v) pervasive;

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Extracting Knowledge From Opinion Mining

opinion mining. Extracting Knowledge From Opinion Mining is an essential resource that presents detailed information on web mining, business;

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Information Retrieval and Social Media Mining

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Computational Linguistics and Intelligent Text Processing

; information extraction and text mining; information retrieval and question answering; document summarization; and applications.;

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String Processing and Information Retrieval

This book constitutes the refereed proceedings of the 23rd International Symposium on String Processing and Information Retrieval, SPIRE;

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Critical Approaches to Information Retrieval Research

Information retrieval (IR) is considered to be the science of searching for information from a variety of information sources related to;

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Foundations of Intelligent Systems

and selected from 67 submissions. The papers are organized in topical sections on data mining methods; databases, information retrieval;

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Advances in Information Retrieval

discourse, efficiency, evaluation, event mining and summarisation, information extraction, recommender systems, semantic and graph-based models;

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Information Management and Big Data

issues such as data mining, artificial intelligence, Natural Language Processing, information retrieval, machine learning, web mining.;

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Opinion Mining in Information Retrieval

organizations have improved their sales, marketing and strategy, setting up new policies and making decisions based on opinion mining techniques.;

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Graph-based Natural Language Processing and Information Retrieval

natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining;

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Information Management and Big Data

. The papers address issues such as data mining, artificial intelligence, Natural Language Processing, information retrieval, machine learning;

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Chinese Computational Linguistics and Natural Language Processing Based on Natur

on lexical semantics and ontologies; semantics; sentiment analysis, opinion mining and text classification; machine translation;

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Computational Linguistics and Intelligent Text Processing

analysis and emotion detection; opinion mining and social network analysis; natural language generation and text summarization; information;

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Computational Linguistics and Intelligent Text Processing

analysis and emotion detection; opinion mining and social network analysis; natural language generation and text summarization; information;

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Information Retrieval Technology

This book constitutes the refereed proceedings of the 13th Information Retrieval Societies Conference, AIRS 2017, held in Jeju, Korea;

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Statistical Language and Speech Processing

, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semantic Web; information extraction;

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Statistical Language and Speech Processing

and spam filtering; computer-aided translation; corpora and language resources; data mining and semantic web; information extraction;

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Information Retrieval Technology

This book constitutes the refereed proceedings of the 12th Information Retrieval Societies Conference, AIRS 2016, held in Beijing, China;

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Computational Linguistics and Intelligent Text Processing

: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization;

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Ontology-Based Information Retrieval for Healthcare Systems

volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for;

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Introduction to Data Mining and its Applications

, knowledge acquisition, information retrieval, high performance computing and data visualization.;

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Computational Linguistics and Intelligent Text Processing

; opinion mining and sentiment detection; text generation; machine translation and multilingualism; information extraction and information;

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Machine Learning for Text

summarization, information extraction, knowledge graphs, question answering, opinion mining, text segmentation, and event detection. Compared to the;

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Advances in Information Retrieval

, mining social media, digital libraries, efficiency, and information retrieval theory. Also included are 3 tutorial and 4 workshop presentations.;

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