scholarly journals AutoSurvey: Automatic Survey Generation based on a Research Draft

2020 ◽  
Author(s):  
Hen-Hsen Huang
Keyword(s):  
Structure Analysis ◽  
Information Structure ◽  
Intelligent System ◽  
Neural Model ◽  
Literature Survey ◽  
Fine Grained

This work presents AutoSurvey, an intelligent system that performs literature survey and generates a summary specific to a research draft. A neural model for information structure analysis is employed for extracting fine-grained information from the abstracts of previous work, and a novel evolutionary multi-source summarization model is proposed for generating the summary of related work. This system is extremely used for both academic and educational purposes.

scholarly journals DISA: A Scientific Writing Advisor with Deep Information Structure Analysis

2017 ◽  
Author(s):  
Hen-Hsen Huang ◽  
Hsin-Hsi Chen
Keyword(s):  
Neural Network ◽  
Structure Analysis ◽  
Information Structure ◽  
Intelligent System ◽  
Scientific Writing ◽  
Computer Aided ◽  
Network Technologies ◽  
Neural Network Technologies

This paper demonstrates DISA, a higher-level writing assistant system, which analyzes the information structure of abstracts, and retrieves the knowledge according to the research goals from the related work. By incorporating the latest neural-network technologies including linguistically-informed neural-network and autoencoder, we construct an intelligent system which extends the scope of computer-aided writing.

scholarly journals Oxidation Roasting of Fine-Grained Carbonaceous Gold Ore: The Effect of Aeration Rate

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 558
Author(s):  
Hui Li ◽  
Wei Xiao ◽  
Jianping Jin ◽  
Yuexin Han
Keyword(s):  
Structure Analysis ◽  
Crystal Structure Analysis ◽  
Aeration Rate ◽  
Practical Significance ◽  
Gold Ore ◽  
Fine Grained ◽  
Roasting Process ◽  
Chemical Groups ◽  
Fine Carbon ◽  
Fine Gold

The oxidation roasting of carbon-bearing micro-fine gold can eliminate or weaken the robbing effect of carbonaceous materials and clay, and destroy the encapsulation of micro-fine gold. The micropores produced by gas escaping during the roasting process are conducive to the diffusion of leaching agents, thus enhancing the cyanide leaching of gold. In this paper, the influence of the aeration rate during roasting on the leaching rate of fine-grained carbonaceous gold ore and its mechanism were studied using thermodynamic calculations, crystal structure analysis, surface chemical groups and bonds analysis, microporous structure analysis, and surface morphology detection. Under suitable roasting conditions, the carbonaceous and pyrite in the ore are oxidized, while carbonate minerals such as dolomite and calcite as well as clay minerals are decomposed, and the gold-robbing materials lose their activity. The experimental results have theoretical and practical significance for the popularization and application of oxidation roasting technology of fine carbon-bearing gold ore.

Automated Extraction and Presentation of Data Practices in Privacy Policies

2021 ◽  
Vol 2021 (2) ◽  
pp. 88-110
Author(s):  
Duc Bui ◽  
Kang G. Shin ◽  
Jong-Min Choi ◽  
Junbum Shin
Keyword(s):  
User Study ◽  
Personal Information ◽  
Personal Data ◽  
Neural Model ◽  
Automated Analysis ◽  
Entity Recognition ◽  
Automated System ◽  
Privacy Policies ◽  
Fine Grained ◽  
Data Practices

Abstract Privacy policies are documents required by law and regulations that notify users of the collection, use, and sharing of their personal information on services or applications. While the extraction of personal data objects and their usage thereon is one of the fundamental steps in their automated analysis, it remains challenging due to the complex policy statements written in legal (vague) language. Prior work is limited by small/generated datasets and manually created rules. We formulate the extraction of fine-grained personal data phrases and the corresponding data collection or sharing practices as a sequence-labeling problem that can be solved by an entity-recognition model. We create a large dataset with 4.1k sentences (97k tokens) and 2.6k annotated fine-grained data practices from 30 real-world privacy policies to train and evaluate neural networks. We present a fully automated system, called PI-Extract, which accurately extracts privacy practices by a neural model and outperforms, by a large margin, strong rule-based baselines. We conduct a user study on the effects of data practice annotation which highlights and describes the data practices extracted by PI-Extract to help users better understand privacy-policy documents. Our experimental evaluation results show that the annotation significantly improves the users’ reading comprehension of policy texts, as indicated by a 26.6% increase in the average total reading score.

A Prospect on an Intelligent Recommender System

2021 ◽  
Vol 12 (2) ◽  
pp. 25-43
Author(s):  
Pooja ◽  
Vishal Bhatnagar
Keyword(s):  
Recommender System ◽  
User Satisfaction ◽  
Recommendation System ◽  
Intelligent System ◽  
Literature Survey ◽  
Research Papers ◽  
Online Data ◽  
Principle Component ◽  
The Future

User satisfaction is the principle component in the prosperity of a recommender system to provide an exact recommendation within a rational amount of time. The recommendation system is an intelligent system that analyzes the large quantity of online data to predict the patterns. In this paper, various recommendation techniques are described as a literature survey and their classifications are explained based upon the attributes and characteristics required for the recommendation process. The categorization of the recommendation system hinge on the analysis of the research papers and identifies the areas of the future for the development of an intelligent system.

Anatomy of a Counterexample: Extraction from Relative Clauses

2018 ◽  
Vol 49 (2) ◽  
pp. 335-378 ◽  
Author(s):  
Ivy Sichel
Keyword(s):  
Working Memory ◽  
Mandarin Chinese ◽  
Information Structure ◽  
Relative Clauses ◽  
Fine Grained ◽  
Syntactic Theory ◽  
Structural Ambiguity ◽  
Fine Grained Structure ◽  
Lebanese Arabic

Relative clauses (RCs) are considered islands for extraction, yet acceptable cases of overt extraction from RCs have been attested over the years in a variety of languages: Danish, Swedish, Norwegian, Japanese, Hebrew, English, Italian, Spanish, French, and also in Lebanese Arabic and Mandarin Chinese, where covert extraction from an RC is observed. The possibility for extraction has often been presented as evidence against a syntactic theory of locality, and in favor of constraints defined in terms of information structure, or processing limitations and constraints on working memory. Another possibility, still hardly explored, is that locality is determined syntactically, combined with a more fine-grained structure for RCs and a theory of how extraction from this structure interacts with the theory of locality. I argue in favor of the latter approach. I assume the structural ambiguity of RCs and argue that while externally headed RCs do block extraction, extraction is possible, under certain conditions, from a raising RC, and is formally similar to extraction from an embedded interrogative.

scholarly journals Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis

2018 ◽  
Vol 6 ◽  
pp. 17-31 ◽  
Author(s):  
Stefanos Angelidis ◽  
Mirella Lapata
Keyword(s):  
Sentiment Analysis ◽  
Neural Model ◽  
Multiple Instance Learning ◽  
Superior Performance ◽  
Learning Networks ◽  
Scoring Method ◽  
Fine Grained ◽  
Opinion Extraction ◽  
Elicitation Study ◽  
Discourse Units

We consider the task of fine-grained sentiment analysis from the perspective of multiple instance learning (MIL). Our neural model is trained on document sentiment labels, and learns to predict the sentiment of text segments, i.e. sentences or elementary discourse units (EDUs), without segment-level supervision. We introduce an attention-based polarity scoring method for identifying positive and negative text snippets and a new dataset which we call SpoT (as shorthand for Segment-level POlariTy annotations) for evaluating MIL-style sentiment models like ours. Experimental results demonstrate superior performance against multiple baselines, whereas a judgement elicitation study shows that EDU-level opinion extraction produces more informative summaries than sentence-based alternatives.

scholarly journals The use of static light scattering for the structure analysis of radiosensitive polymer gels: a literature survey

2004 ◽  
Vol 3 ◽  
pp. 180-183 ◽  
Author(s):  
E Vanden Bussche ◽  
Y De Deene ◽  
P Dubruel ◽  
K Vergote ◽  
E Schacht ◽  
...  
Keyword(s):  
Light Scattering ◽  
Structure Analysis ◽  
Polymer Gels ◽  
Literature Survey ◽  
Static Light Scattering

On identifiability and definiteness in English and German

2008 ◽  
Vol 8 (2) ◽  
pp. 263-285
Author(s):  
Carsten Breul
Keyword(s):  
Structure Analysis ◽  
Information Structure ◽  
Initial Position ◽  
Definite Article ◽  
Contrastive Analysis ◽  
Focus Structure ◽  
Structural Category ◽  
Guiding Questions

Despite increasingly numerous works dealing with issues of information structure from a cross-linguistic perspective, contrastive information structure analysis is not an established field of research yet. The paper aims at showing that it is worthwhile staking out and exploring such a field. Starting off from a brief reminder of what information structure is, as conceived of by Lambrecht (1994), the paper proposes guiding questions that contrastive information structure analysis should strive to answer. It then turns to the discussion of an example of contrastive analysis which involves the information structural category of identifiability. It is argued that the variable x in the English formula ‘as for x’ and the corresponding German formula was x {(an)betrifft / angeht} in sentence initial position can only be instantiated by expressions that have identifiable discourse referents. Results of a corpus-based comparison of expressions which instantiate x in these English and German formulas are presented. These results show contrasts between English and German in the lexicogrammatical expression of identifiable referents that go beyond the better-known differences in the use of the definite article. A methodological point to be made is that Lambrechtian categories of information structure (identifiability and activation of discourse referents, focus structure) may serve as tertia comparationis for the analysis of contrasts on the lexicogrammatical level.

scholarly journals Information Structure and Scope Interactions: Disjunction Wide Scope Induced by Focus

2021 ◽  
Vol 5 ◽  
Author(s):  
Cécile Larralde ◽  
Alina Konradt ◽  
Kriszta Eszter Szendrői
Keyword(s):  
Information Structure ◽  
Wide Scope ◽  
Value Judgment ◽  
Fine Grained ◽  
Narrow Scope ◽  
Subject Design ◽  
Truth Value ◽  
Scope Interactions ◽  
Scope Reading ◽  
Prosodic Focus

In this paper we investigate the scopal reading of disjunctions in French negative sentences with pre-schoolers. We posit that the French disjunctor “ou” does not fit the traditional disjunction PPI/non-PPI dichotomy according to which a wide scope is taken by a PPI disjunction and a narrow scope when the disjunction is not a PPI. We hypothesized that focus could be a succesful scopal manipulator. Using Truth Value Judgment Tasks (TVJT), we tested French pre-schoolers' scopal reading of negated disjunctions in a neutral prosody condition and with prosodic focus on the disjunctor in a between subject design. We found that as predicted, prosodic focus often enduced participants to adopt a disjunction wide scope reading whereas a disjunction narrow scope reading was favored in the neutral prosody condition. This confirmed our hypothesis that focus can manipulate disjunction scope paramaters. It also shows that, when the disjunction is focalised, children have access to the disjunction wide scope reading earlier than previously thought. Finally, we can conclude that the distinction between PPI-disjunctor vs. non-PPI disjunctor languages needs to be more fine-grained.

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