scholarly journals Sequeval: An Offline Evaluation Framework for Sequence-Based Recommender Systems

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 174 ◽  
Author(s):  
Diego Monti ◽  
Enrico Palumbo ◽  
Giuseppe Rizzo ◽  
Maurizio Morisio
Keyword(s):  
Recommender Systems ◽  
Random Fields ◽  
Conditional Random Fields ◽  
State Of The Art ◽  
Focal Point ◽  
Objective Evaluation ◽  
Lessons Learned ◽  
Evaluation Framework ◽  
Definition Of ◽  
The Right

Recommender systems have gained a lot of popularity due to their large adoption in various industries such as entertainment and tourism. Numerous research efforts have focused on formulating and advancing state-of-the-art of systems that recommend the right set of items to the right person. However, these recommender systems are hard to compare since the published evaluation results are computed on diverse datasets and obtained using different methodologies. In this paper, we researched and prototyped an offline evaluation framework called Sequeval that is designed to evaluate recommender systems capable of suggesting sequences of items. We provide a mathematical definition of such sequence-based recommenders, a methodology for performing their evaluation, and the implementation details of eight metrics. We report the lessons learned using this framework for assessing the performance of four baselines and two recommender systems based on Conditional Random Fields (CRF) and Recurrent Neural Networks (RNN), considering two different datasets. Sequeval is publicly available and it aims to become a focal point for researchers and practitioners when experimenting with sequence-based recommender systems, providing comparable and objective evaluation results.

scholarly journals Guiding Attention in Sequence-to-Sequence Models for Dialogue Act Prediction

2020 ◽  
Vol 34 (05) ◽  
pp. 7594-7601
Author(s):  
Pierre Colombo ◽  
Emile Chapuis ◽  
Matteo Manica ◽  
Emmanuel Vignon ◽  
Giovanna Varni ◽  
...  
Keyword(s):  
Machine Translation ◽  
Random Fields ◽  
Conditional Random Fields ◽  
State Of The Art ◽  
The State ◽  
Attention Mechanism ◽  
Accuracy Score ◽  
Beam Search ◽  
Conversational Agents ◽  
Neural Machine Translation

The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents. Accurately predicting DAs requires a precise modeling of both the conversation and the global tag dependencies. We leverage seq2seq approaches widely adopted in Neural Machine Translation (NMT) to improve the modelling of tag sequentiality. Seq2seq models are known to learn complex global dependencies while currently proposed approaches using linear conditional random fields (CRF) only model local tag dependencies. In this work, we introduce a seq2seq model tailored for DA classification using: a hierarchical encoder, a novel guided attention mechanism and beam search applied to both training and inference. Compared to the state of the art our model does not require handcrafted features and is trained end-to-end. Furthermore, the proposed approach achieves an unmatched accuracy score of 85% on SwDA, and state-of-the-art accuracy score of 91.6% on MRDA.

scholarly journals Waterfall Atrous Spatial Pooling Architecture for Efficient Semantic Segmentation

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5361 ◽  
Author(s):  
Bruno Artacho ◽  
Andreas Savakis
Keyword(s):  
Random Fields ◽  
Conditional Random Fields ◽  
State Of The Art ◽  
Semantic Segmentation ◽  
Training Time ◽  
Network Parameters ◽  
Spatial Pooling ◽  
Memory Footprint ◽  
Accuracy Increase ◽  
Spatial Pyramid

We propose a new efficient architecture for semantic segmentation, based on a “Waterfall” Atrous Spatial Pooling architecture, that achieves a considerable accuracy increase while decreasing the number of network parameters and memory footprint. The proposed Waterfall architecture leverages the efficiency of progressive filtering in the cascade architecture while maintaining multiscale fields-of-view comparable to spatial pyramid configurations. Additionally, our method does not rely on a postprocessing stage with Conditional Random Fields, which further reduces complexity and required training time. We demonstrate that the Waterfall approach with a ResNet backbone is a robust and efficient architecture for semantic segmentation obtaining state-of-the-art results with significant reduction in the number of parameters for the Pascal VOC dataset and the Cityscapes dataset.

scholarly journals Beyond Word Attention: Using Segment Attention in Neural Relation Extraction

2019 ◽  
Author(s):  
Bowen Yu ◽  
Zhenyu Zhang ◽  
Tingwen Liu ◽  
Bin Wang ◽  
Sujian Li ◽  
...  
Keyword(s):  
Random Fields ◽  
Latent Variables ◽  
Large Scale ◽  
Conditional Random Fields ◽  
Marginal Distribution ◽  
State Of The Art ◽  
Linear Chain ◽  
Relation Extraction ◽  
Word Attention ◽  
Attention Weight

Relation extraction studies the issue of predicting semantic relations between pairs of entities in sentences. Attention mechanisms are often used in this task to alleviate the inner-sentence noise by performing soft selections of words independently. Based on the observation that information pertinent to relations is usually contained within segments (continuous words in a sentence), it is possible to make use of this phenomenon for better extraction. In this paper, we aim to incorporate such segment information into neural relation extractor. Our approach views the attention mechanism as linear-chain conditional random fields over a set of latent variables whose edges encode the desired structure, and regards attention weight as the marginal distribution of each word being selected as a part of the relational expression. Experimental results show that our method can attend to continuous relational expressions without explicit annotations, and achieve the state-of-the-art performance on the large-scale TACRED dataset.

Diversity in logarithmic opinion pools

2007 ◽  
Vol 30 (1) ◽  
pp. 27-47 ◽  
Author(s):  
Andrew D.M. Smith ◽  
Miles Osborne
Keyword(s):  
Random Fields ◽  
Conditional Random Fields ◽  
State Of The Art ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Improve Performance ◽  
Named Entity ◽  
Underlying Theory ◽  
Opinion Pool ◽  
Weighted Combination

Conditional random fields are state-of-the-art models for sequencing tasks such as named entity recognition. However, being globally conditioned, they have a tendency to overfit to a greater extent than other sequencing models. We introduce an approach to combat this overfitting called a logarithmic opinion pool (LOP). A LOP consists of a weighted combination of constituent models. We present the theory behind LOPs, and show that effective LOPs require constituent models that are diverse from one another. We examine different ways to introduce such diversity, including an approach that involves training the constituent models together, interactively. Our results show that, as expected from the underlying theory, explicitly optimising for constituent model diversity can improve performance over standard approaches to regularisation.

A SURVEY OF CONTEXT-AWARE MOBILE RECOMMENDATIONS

2013 ◽  
Vol 12 (01) ◽  
pp. 139-172 ◽  
Author(s):  
QI LIU ◽  
HAIPING MA ◽  
ENHONG CHEN ◽  
HUI XIONG
Keyword(s):  
Recommender Systems ◽  
User Interfaces ◽  
State Of The Art ◽  
Contextual Information ◽  
General Notion ◽  
Context Aware ◽  
Key Issues ◽  
Privacy Problem ◽  
Mobile Context ◽  
The Right

Mobile recommender systems target on recommending the right product or information to the right mobile users at anytime and anywhere. It is well known that the contextual information is often the key for the performances of mobile recommendations. Therefore, in this paper, we provide a focused survey of the recent development of context-aware mobile recommendations. After briefly reviewing the state-of-the-art of recommender systems, we first discuss the general notion of mobile context and how the contextual information is collected. Then, we introduce the existing approaches to exploit contextual information for modeling mobile recommendations. Furthermore, we summarize several existing recommendation tasks in the mobile scenarios, such as the recommendations in the tourism domain. Finally, we discuss some key issues that are still critical in the field of context-aware mobile recommendations, including the privacy problem, the energy efficiency issues, and the design of user interfaces.

scholarly journals Data Ownership: A Survey

Information ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 465
Author(s):  
Jad Asswad ◽  
Jorge Marx Gómez
Keyword(s):  
State Of The Art ◽  
Smart Cities ◽  
Lessons Learned ◽  
Future Research ◽  
Transportation Industry ◽  
Privacy And Security ◽  
Data Ownership ◽  
The Subject ◽  
Definition Of ◽  
Innovation Knowledge

The importance of data is increasing along its inflation in our world today. In the big data era, data is becoming a main source for innovation, knowledge and insight, as well as a competitive and financial advantage in the race of information procurement. This interest in acquiring and exploiting data, in addition to the existing concerns regarding the privacy and security of information, raises the question of who should own the data and how the ownership of data can be preserved. This paper discusses and analyses the concept of data ownership and provides an overview on the subject from different point of views. It surveys also the state-of-the-art of data ownership in health, transportation, industry, energy and smart cities sectors and outlines lessons learned with an extended definition of data ownership that may pave the way for future research and work in this area.

scholarly journals Pathological Analysis of the Charter of Citizenship Rights in Iran in Judicial Rights Terms with a Focus on Human Dignity

2016 ◽  
Vol 10 (1) ◽  
pp. 177
Author(s):  
Fatemeh Piraman ◽  
Seyed Mohammad Sadegh Ahmadi ◽  
Masoud Raei
Keyword(s):  
Human Dignity ◽  
Focal Point ◽  
Legal Rights ◽  
Constitutional Rights ◽  
Citizenship Rights ◽  
Constitutional Right ◽  
Legal Security ◽  
Definition Of ◽  
The Right

Judicial right is one of the most significant fields of citizenship rights. A large part of the right legal instances become considerable when a citizen is under suspicion. To codify the examples of legal rights principally, the concept of human dignity needs to be the focal point on a constant basis. In the case of ignoring this criterion in arranging the constitutional rights the justice would not be attained, and the legal security of the citizens would be disrupted.Within the constitutional rights of Iran, the charter of the citizenship rights as a comprehensive document considered within the constitutional right field.  In the preface and principles of this document human dignity is confirmed as one of the most significant factors in codifying the citizenship rights. However, in the continuation and in the arrangement of the instances of the citizenship rights this criterion has not been considered as expected.The charter of the constitutional rights compared to previous rules of it has no significant innovation. Two groups of factors have caused the insignificant role of human dignity within the judicial rights. The first groups include the general factors such as presenting an inaccurate definition of citizen and mingling the instances of human rights with examples of rights. The second group of factors that mostly relate the lack of precise positioning towards some of the accepted principles of the legal right has provided the possibility of violating human dignity in this charter.

THE CONCEPT OF CONSTITUTIONAL AND LEGAL GUARANTEES OF ELECTORAL RIGHTS

2020 ◽  
Vol 10 (4) ◽  
pp. 85-90
Author(s):  
VLADIMIR TROYAN ◽  
Keyword(s):  
Scientific Research ◽  
Formal Aspect ◽  
Universal Approach ◽  
Right To Vote ◽  
Definition Of ◽  
The Right

The relevance of the interpretation of constitutional and legal guarantees of the right to vote is mediated by isolated scientific research in this area, as well as the lack of a universal approach to legal guarantees. In this regard, the purpose of the article is to argue and disclose the author’s definitive aspect of the claimed guarantees. In the work, the author named and characterized the normative (based exclusively on legal means) with the perspective of a branch of legal and technical; regulatory and institutional (combines the formal aspect with the activities of authorized entities) and associated legal (including a set of legal and other aspects) approaches to the definition of legal guarantees. Based on the second approach, as well as combining the guarantees of the right to vote directly guarantees of the subjective right itself and guarantees of its implementation, the author offers a definition of constitutional and legal guarantees of the right to vote.

cMOOCs and Global Learning: An Authentic Alternative

2013 ◽  
Vol 17 (2) ◽  
Author(s):  
Carol Yeager ◽  
Betty Hurley-Dasgupta ◽  
Catherine A. Bliss
Keyword(s):  
Online Courses ◽  
Lessons Learned ◽  
Massive Open Online Courses ◽  
Research Review ◽  
Press Coverage ◽  
Open Educational Resource ◽  
Educational Resource ◽  
Global Learning ◽  
Massive Open Online ◽  
Definition Of

Massive Open Online Courses (MOOCs) continue to attract press coverage as they change almost daily in their format, number of registrations and potential for credentialing. An enticing aspect of the MOOC is its global reach. In this paper, we will focus on a type of MOOC called a cMOOC, because it is based on the theory of connectivism and fits the definition of an Open Educational Resource (OER) identified for this special edition of JALN. We begin with a definition of the cMOOC and a discussion of the connectivism on which it is based. Definitions and a research review are followed with a description of two MOOCs offered by two of the authors. Research on one of these MOOCs completed by a third author is presented as well. Student comments that demonstrate the intercultural connections are shared. We end with reflections, lessons learned and recommendations.

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