Challenge: Graph databases are well-suited for crossreferencing information from multiple sources to support machine learning tasks.
Approach: They propose a graph-based structure of multiple resources enriched with graph analytics approaches to provide an encompassing view of the movie recommendation domain and of the way people talk about it during the recommendation task.
Outcome: The proposed graph-based structure provides an encompassing view of the domain and of the way people talk about it during the recommendation task.

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Challenge: Existing algorithms for recommending items are limited and focused on specific domains.
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What’s This Movie About? A Joint Neural Network Architecture for Movie Content Analysis (N18-1)

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Challenge: Using movie overviews, we can gain a general impression of a movie by summarizing its content, genre, and artistic style.
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Graph-Based Meaning Representations: Design and Processing (P19-4)

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Challenge: This tutorial focuses on representing and processing sentence meaning in the form of labeled directed graphs.
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Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13) (D19-53)

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Challenge: TextGraphs is a workshop on graph-based methods for natural language processing . the workshop is being organized in conjunction with the 9th International Joint Conference on Natural Language Processing .
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Challenge: a corpus of movie plot synopses and tags can be used to build automatic tagging systems . a method to collect these tags allows us to learn to predict tags from plot synoopsis .
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Challenge: Existing approaches to intent prediction are limited in highly specialized fields, such as closed-domain dialogue systems, where context comprehension is of paramount importance.
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Conversation Graph: Data Augmentation, Training, and Evaluation for Non-Deterministic Dialogue Management (2021.tacl-1)

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Challenge: Existing datasets limited in size con- sidering complexity of dialogues . current trends lean towards end-to-end models while modular systems tend to be preferred in industrial applications.
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EMTC: Multilabel Corpus in Movie Domain for Emotion Analysis in Conversational Text (L18-1)

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Challenge: Existing emotion corpora collected from twitters and use hashtags are limited in the number of characters.
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Recommendation Chart of Domains for Cross-Domain Sentiment Analysis: Findings of A 20 Domain Study (2020.lrec-1)

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Challenge: Cross-domain sentiment analysis (CDSA) is a well-known problem in text analysis, but sufficient datasets may not be available for a domain to be trained.
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