Mining Latent Entity Structures by Chi Wang
The big data era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions.-
Deep Learning for Polymer Discovery
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Provenance Data in Social Media
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Mining Structures of Factual Knowledge from Text
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Exploratory Causal Analysis with Time Series Data
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Probabilistic Approaches to Recommendations
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Detecting Fake News on Social Media
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Phrase Mining from Massive Text and Its Applications
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Modeling and Data Mining in Blogosphere
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Outlier Detection for Temporal Data
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Privacy in Social Networks
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Correlation Clustering
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Exploiting the Power of Group Differences
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Multidimensional Mining of Massive Text Data
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Individual and Collective Graph Mining
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Automated Taxonomy Discovery and Exploration
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Graph Mining
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Advances in Graph Neural Networks
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Mining Human Mobility in Location-Based Social Networks
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Ensemble Methods in Data Mining
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Mining Heterogeneous Information Networks
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Community detection and mining in social media
Jiawei Han is a professor at the University of Illinois at Urbana-Champaign's Department of Computer Science. He is well-known for his work in data mining and database systems, and has received numerous honors for his efforts, including the 2004 ACM SIGKDD Innovations Award. He has served on the editorial boards of many publications, including IEEE Transactions on Knowledge and Data Engineering and Data Mining and Knowledge Discovery, and as Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data.
| SKU | Unavailable |
| ISBN 13 | 9783031007798 |
| ISBN 10 | 3031007794 |
| Title | Mining Latent Entity Structures |
| Author | Chi Wang |
| Series | Synthesis Lectures On Data Mining And Knowledge Discovery |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2015-04-01 |
| Number of pages | 147 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |