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Entity Network Prediction Using Multitype Topic Models
2008
IEICE transactions on information and systems
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We show that this multitype topic model performs better at making predictions on entity networks, in which each vertex represents an entity and each edge weight represents how a pair of entities at the ...
Statistical models that capture dependencies between named entities and topics can play an important role. ...
Acknowledgements We thank Giridhar Kumaran, University of Massachusetts Amherst, for providing the annotation data. ...
doi:10.1093/ietisy/e91-d.11.2589
fatcat:ccrbafp6i5gedkxceeyhk3iwia
Uncertainty Reduction for Knowledge Discovery and Information Extraction on the World Wide Web
2012
Proceedings of the IEEE
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What types of interactions can be conducted between these techniques and information networks to make them benefit from each other? ...
What are the fundamental techniques that can be used to reduce such uncertainty and achieve reasonable KD and IE performance on the WWW? What is the impact of each novel method? ...
In [55] , we address these issues as suffered from traditional topic modeling and intent to discover latent semantic topics and reinforce clusters of multityped objects simultaneously. ...
doi:10.1109/jproc.2012.2190489
fatcat:4rye7lknyvbe5ggxtpv7fqptgm
Towards Conversational Recommendation over Multi-Type Dialogs
[article]
2020
arXiv
pre-print
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Dataset and codes are publicly available at https://github.com/PaddlePaddle/models/tree/develop/PaddleNLP/Research/ACL2020-DuRecDial. ...
This dataset allows us to systematically investigate different parts of the overall problem, e.g., how to naturally lead a dialog, how to interact with users for recommendation. ...
Acknowledgments We would like to thank Ying Chen for dataset annotation and thank Yuqing Guo and the reviewers for their insightful comments. ...
arXiv:2005.03954v3
fatcat:d4bjogeowza7jggeeveilaybrq
Constructing topical hierarchies in heterogeneous information networks
2014
Knowledge and Information Systems
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Contrary to traditional text-based topic modeling, our approach handles both textual phrases and multiple types of entities by a newly designed clustering and ranking algorithm for heterogeneous network ...
A digital data collection (e.g., scientific publications, enterprise reports, news, and social media) can often be modeled as a heterogeneous information network, linking text with multiple types of entities ...
However, CATHY heuristic HIN first constructs phraserepresented topics from text, and then uses entity link information to rank entities in each topic. ...
doi:10.1007/s10115-014-0777-4
fatcat:exhvtiyr7nd4nhshh5kf2uoiau
Constructing Topical Hierarchies in Heterogeneous Information Networks
2013
2013 IEEE 13th International Conference on Data Mining
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Contrary to traditional text-based topic modeling, our approach handles both textual phrases and multiple types of entities by a newly designed clustering and ranking algorithm for heterogeneous network ...
A digital data collection (e.g., scientific publications, enterprise reports, news, and social media) can often be modeled as a heterogeneous information network, linking text with multiple types of entities ...
However, CATHY heuristic HIN first constructs phraserepresented topics from text, and then uses entity link information to rank entities in each topic. ...
doi:10.1109/icdm.2013.53
dblp:conf/icdm/WangDLDJH13
fatcat:rfn4w3f7ufeg5fw7asip4exxfy
Survey on entity linking for domain specific with heterogeneous information networks
2019
Informatologia
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The entity linkage determines the corresponding entities from unstructured web text, in the existing HIN. ...
Entity linking is a task of extracting information that links the mentioned entity in a collection of text with their similar knowledge base as well as it is the task of allocating unique identity to various ...
This model captured the entity popularity and the handling of multitype objects model appeared in the textual context. ...
doi:10.32914/i.52.3-4.5
fatcat:zd2ypopvpjfqnd3xw4tg57uuh4
Exploiting Synchronicity Networks for Finding Valuables in Heterogeneous Networks
[chapter]
2013
Proceedings of the 2013 SIAM International Conference on Data Mining
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Furthermore, based on the synchronicity networks, we propose a novel algorithm for Heterogeneous Multi-level networks Ranking, to simultaneously rank inter-related heterogeneous entities (e.g., topics, ...
Account team CS Sociology SNA EE Sensor Team level network Person level network Delivery team Engineering team Design team Healthcare Information topic level network 1 We use the terms "entity" and "object ...
For a preliminary validation of our approach in social media context, we use a subset of annotated Twitter dataset from [4] . It contains 70K tweets from 344 Twitter user accounts in 2010. ...
doi:10.1137/1.9781611972832.41
dblp:conf/sdm/LinW13
fatcat:zwe45dxqlbfgvickuvqhueoxoq
Mining latent entity structures from massive unstructured and interconnected data
2014
Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14
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The framework enables recursive construction of phrase-represented and entity-enriched topic hierarchy from text-attached information networks. ...
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. ...
However, CATHY heuristic HIN first constructs phrase-represented topics from text, and then uses entity link information to rank entities in each topic. ...
doi:10.1145/2588555.2588890
dblp:conf/sigmod/HanW14
fatcat:js7d3r5yd5gbfgnhjgwsfmco2i
Automatic wrappers for large scale web extraction
2011
Proceedings of the VLDB Endowment
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This enables us to learn wrappers in a completely unsupervised manner from automatically and cheaply obtained noisy training data, e.g., using dictionaries and regular expressions. ...
Our system is used in production at Yahoo! and powers live applications. ...
The P(X) component of our ranking, that models the goodness of a list, is not applicable for single-entity extraction. ...
doi:10.14778/1938545.1938547
fatcat:i7f4ecwnx5gqzntssqw2vapsc4
Aemoo: Linked Data exploration based on Knowledge Patterns
2016
Semantic Web Journal
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EKP are discovered by mining the linking structure of Wikipedia and evaluated by means of a user-based study, which shows that they are cognitively sound as models for building entity summarisations. ...
We implemented a tool named Aemoo that supports EKP-driven knowledge exploration and integrates data coming from heterogeneous resources, namely static and dynamic knowledge as well as text and Linked ...
Thus, Aemoo extracts this piece of text (with a maximum of 50 words) and enriches the model with an OWL2 annotation representing this linguistic evidence. ...
doi:10.3233/sw-160222
fatcat:7jfqevtwv5dr5h5w6zokkkok2q
Towards Deep Learning Prospects: Insights for Social Media Analytics
2019
IEEE Access
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Deep learning (DL) has attracted increasing attention on account of its significant processing power in tasks, such as speech, image, or text processing. ...
His research interests include data mining, social network analysis and mining, probabilistic models, scientometrics, and natural language processing. ...
In terms of SM insights, the text is still a dominating factor among multityped data. ...
doi:10.1109/access.2019.2905101
fatcat:65mxyey3frdrfngvbfnfss3gpa
A Probabilistic Approach to Personalized Tag Recommendation
2010
2010 IEEE Second International Conference on Social Computing
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We evaluate the proposed framework on a benchmark dataset collected from BibSonomy, and compare with two groups of baseline methods: (i) personomy translation methods based solely on the query user; and ...
We propose to use distributional divergence to measure the similarity between users in the context of personomy translation, and examine two variations of such divergence (similarity) measures. ...
Data Collection Our datasets are collected from BibSonomy [11] . Snapshots of BibSonomy have also been used as benchmark datasets in the PKDD ECML Discovery Challenge 2009. ...
doi:10.1109/socialcom.2010.15
dblp:conf/socialcom/HuLJ10
fatcat:nrhjgyaudzf5vjiiwwdsalpsbi
Personalized Abstractive Opinion Tagging
2022
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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review graph to track user preferences from reviews; (2) a behavior-based implicit preference tracker component using a heterogeneous behavior graph to track the user preferences from implicit behaviors ...
In our experiments, we evaluate POT on a real-world dataset collected from e-commerce platforms and the results demonstrate that it significantly outperforms strong baselines. ...
For text pre-processing, we tokenize texts using the Jieba toolkit 4 and remove words with low-frequency. We finally get a vocabulary of size 44k. ...
doi:10.1145/3477495.3532037
fatcat:vfnqzfghvzhfvfbeje4m6i2e54
Exploiting Background Information Networks to Enhance Bilingual Event Extraction Through Topic Modeling
unpublished
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Based on this intuition, we apply topic modeling to automatically select training documents for annotation, and demonstrate it can significantly reduce annotation cost in order to achieve comparable performance ...
In this paper, we describe a novel approach of biased propagation based topic modeling to exploit global background knowledge for enhancing both the quality and portability of event extraction on unstructured ...
The texts are automatically annotated with word segmentation, part-of-speech tags, parsing structures, entities, time expressions, and relations. ...
fatcat:vfps6fb4ibezvnz7b6by2flpky
Towards Conversational Recommendation over Multi-Type Dialogs
2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
unpublished
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This dataset allows us to systematically investigate different parts of the overall problem, e.g., how to naturally lead a dialog, how to interact with users for recommendation. ...
We focus on the study of conversational recommendation in the context of multi-type dialogs, where the bots can proactively and naturally lead a conversation from a nonrecommendation dialog (e.g., QA) ...
Acknowledgments We would like to thank Ying Chen for dataset annotation and thank Yuqing Guo and the reviewers for their insightful comments. ...
doi:10.18653/v1/2020.acl-main.98
fatcat:r6xy7uu4ozc4lkmnb3bxg26ni4
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