Tuple Extraction – Meta-Guide.com

Notes:

Tuple extraction is a natural language processing (NLP) technique that is used to identify and extract specific pieces of information from natural language text. This is typically accomplished using a combination of linguistic analysis and machine learning algorithms, which are trained to identify and extract specific types of information from the input text.

Attribute triples extraction (ATE) is a natural language processing (NLP) technique that is used to identify and extract specific types of information from natural language text. In particular, ATE is used to extract triples of the form (subject, attribute, value), where the subject is the entity being described, the attribute is the property of the entity being described, and the value is the specific value of the property. For example, an ATE system might extract the triple (John, height, 6 feet) from the sentence “John is 6 feet tall.”

ATE is typically used to extract structured information from unstructured text, such as news articles, documents, or social media posts. This information can then be used for a variety of purposes, such as building knowledge graphs, improving search results, or generating summaries of text. ATE is often used in combination with other NLP techniques, such as named entity recognition and part-of-speech tagging, to improve the accuracy and effectiveness of the extraction process.

Open relation triples extraction (ORTE) is a natural language processing (NLP) technique that is used to identify and extract specific types of information from natural language text. In particular, ORTE is used to extract triples of the form (subject, relation, object), where the subject is the entity that is related to the object, the relation is the type of relationship between the subject and the object, and the object is the entity that the subject is related to. For example, an ORTE system might extract the triple (John, loves, Mary) from the sentence “John loves Mary.”

ORTE is typically used to extract relational information from unstructured text, such as news articles, documents, or social media posts. This information can then be used for a variety of purposes, such as building knowledge graphs, improving search results, or generating summaries of text. ORTE is often used in combination with other NLP techniques, such as named entity recognition and part-of-speech tagging, to improve the accuracy and effectiveness of the extraction process.

In the context of dialog systems, tuple extraction could be used to identify and extract key information from user inputs. For example, tuple extraction could be used to identify the main topic or intent of a user’s input, or to extract specific pieces of information that are relevant to the dialog context, such as dates, times, locations, or other entities. This information could then be used by the dialog system to generate an appropriate response, or to perform actions based on the user’s input.

Resources:

heartofgold.dfki.de .. a middleware architecture for the integration of deep and shallow natural language processing components

Wikipedia:

Relationship extraction

References:

Advances in deep parsing of scholarly paper content (2009)

RDF triples extraction from company web pages: comparison of state-of-the-art Deep Models
B Wouter, F PORTET, H MIRISAEE, L Cyril – ceur-ws.org
Relation extraction (RE) is a promising way to extend the semantic web from web pages. However, it is unclear how RE can deal with the several challenges of web pages such as noise, data sparsity and conflicting information. In this paper, we benchmark state-of-the-art …

Open domain Chinese triples hierarchical extraction method
C He, Z Tan, H Wang, C Zhang, Y Hu, B Ge – Applied Sciences, 2020 – mdpi.com
… Abstract. Open domain relation prediction is an important task in triples extraction. When … successful. In recent years, in particular, supervised learning models have greatly promoted the development of specific relation triples extraction …

Crowdsourcing-based Data Extraction from Visualization Charts
C Chai, G Li, J Fan, Y Luo – 2020 IEEE 36th International …, 2020 – ieeexplore.ieee.org
… Specifically, we design four types of crowdsourcing tasks that can be categorized into two groups, ie, the preprocessing tasks and tuple extraction task, as illustrated in Fig … (4) Tuple extraction task. The central task for chart data extraction is to identify the tuples …

The Joint Ontology Workshops Proceedings of the Joint Ontology Workshops co-located with the Bolzano Summer of Knowledge (BOSK 2020)
K Hammar, O Kutz, A Dimou, T Hahmann, R Hoehndorf… – 2020 – biblio.ugent.be
… Preface DeepOntoNLP: Deep Learning meets Ontologies and Natural Language Processing — 1st International Workshop RDF triples extraction from company web pages: comparison of state-of-the-art Deep Models Wouter Baes, François Portet, Hamid Mirisaee, Cyril Labbé …

Biomedical knowledge graphs construction from conditional statements
T Jiang, Q Zeng, T Zhao, B Qin, T Liu… – … ACM transactions on …, 2020 – ieeexplore.ieee.org
… designed tag schema. We design a Multi-Input Multi-Output sequence labeling model (MIMO) that learns from multiple input signals and generates proper number of multiple output sequences for tuple extraction. Experiments on …

SETLBI: An Integrated Platform for Semantic Business Intelligence
RP Deb Nath, K Hose, TB Pedersen… – … Proceedings of the …, 2020 – dl.acm.org
… setl:SemanticSource Extractor Extraction Operations setl:DBExtractor RDF Triples Extraction Operations setl:RDFWrapper setl:SemanticSource Extractor Extraction Operations setl:DBExtractor RDF Triples Extraction Operations setl:source ABox …

Semantic Oriented Text Clustering Based on RDF
S Fatimi, C El Saili, L Alaoui – 2020 International Conference on …, 2020 – ieeexplore.ieee.org
… The preprocessing phase is vital before addressing the triples extraction, usually, sentence parsers that can be used for the triples extraction cannot handle some … These issues can be handled during the preprocessing phase to prepare the sentences for the RDF extraction …

Leveraging the Pattern-Relation Duality for Domain-specific Keyphrase Mining
D Ray – diproray.com
… specific keyphrase mining. We adapt a previous framework for tuple extraction over the web (PRDualRank) to our problem, then extend it using a public knowledge base (Wikipedia) and a phrasal segmentation system. We further …

Effective modeling of encoder-decoder architecture for joint entity and relation extraction
T Nayak, HT Ng – Proceedings of the AAAI Conference on Artificial …, 2020 – ojs.aaai.org
… This new decoding framework helps in speeding up the training pro- cess and uses less resources (GPU memory). This will be an important factor when we move from sentence-level tuple extraction to document-level extraction …

Effective risk positioning through automated identification of missing contract conditions from the contractor’s perspective based on FIDIC contract cases
JH Lee, Y Ham, JS Yi, JW Son – Journal of Management in …, 2020 – ascelibrary.org
… Step 3. Subject, verb, and object (SVO) tuple extraction: risk identification elements (ie, SVO tuple) are … Identifying contractor- friendly clause Contract Conditions Text pre-processing using simplification rules SVO tuple extraction Semantic analysis Step 1 Step 2 Step 3 Step 4 …

Mapping natural language instructions to mobile ui action sequences
Y Li, J He, X Zhou, Y Zhang, J Baldridge – arXiv preprint arXiv:2005.03776, 2020 – arxiv.org
… 4.1 Phrase Tuple Extraction Model … Decoder ? ? ? ? ? r j q o j q u j q b:d h it j q Figure 3: The Phrase Tuple Extraction model encodes the instruction’s token sequence and then outputs a tuple sequence by querying into all possible spans of the encoded sequence …

Improving ERP Integration
II MAJOR – researchgate.net
… These logical mappings share a common merging phase with initial independent tuple extraction and fragment-generation phase. [7] … The first phase is the tuple extraction whereby the result is a table of flat tuples obtained from various possibilities of the instances …

An Advanced BERT-Based Decomposition Method for Joint Extraction of Entities and Relations
C Wang, A Li, H Tu, Y Wang, C Li… – 2020 IEEE Fifth …, 2020 – ieeexplore.ieee.org
… Firstly, the BERT pre-training model is introduced to model the text more finely. Next ? We decompose triples extraction into two subtasks: head entity extraction and tail entity extraction, which solves the problem of single entity overlap in the triples …

CrowdChart: Crowdsourced Data Extraction from Visualization Charts
C Chai, G Li, J Fan, Y Luo – IEEE Transactions on Knowledge …, 2020 – ieeexplore.ieee.org
… Thus, we will not elaborate these tasks and focus on a more challenging tuple extraction task as below. Tuple extraction task … We design a tuple extraction task that crowdsources an entire tuple instead of putting values of a tuple in different tasks. The reason is two-fold …

KGen: a knowledge graph generator from biomedical scientific literature
A Rossanez, JC Dos Reis… – BMC Medical …, 2020 – bmcmedinformdecismak …
Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational help. For example, Alzheimer’s Disease …

Scratch-DKG: A Framework for Constructing Scratch Domain Knowledge Graph
P Qi, Y Sun, H Luo, M Guizani – IEEE Transactions on …, 2020 – ieeexplore.ieee.org
… According to the domain characteristics of Scratch, we aim at the triples extraction from different types of data … 3) Template Matching and Triples Extraction: Before extracting triples from new webpages, we define a Webpage Structure Similarity formula using Equation (2) …

Multivariate Modelling of the Trace Element Chemistry of Arsenopyrite from Gold Deposits Using Higher-Dimensional Algebras
S Thiruvengadam, ME Murphy, JS Tan… – Mathematical …, 2020 – Springer
Page 1. Math Geosci https://doi.org/10.1007/s11004-020-09856-3 Multivariate Modelling of the Trace Element Chemistry of Arsenopyrite from Gold Deposits Using Higher-Dimensional Algebras Sudharsan Thiruvengadam1,2 · Matthew Edmund Murphy1 …

KnowText: Auto-generated Knowledge Graphs for custom domain applications
T Matthews, JK Sasikumar, B Boži? – 2020 – openreview.net
… Both the extracted triples and the OWL ontology files can be downloaded and further explored. The two processes of triples extraction and ontology generation are performed in parallel using a succession of NLP techniques. Fig …

Building a knowledge graph by using cross-lingual transfer method and distributed MinIE algorithm on apache spark
P Do, T Phan, H Le, BB Gupta – Neural Computing and Applications, 2020 – Springer
… We borrow tools for processing English text such as Stanford Parser for dependency parsing, NeuralCoref for co-referencing, ClausIE, and MinIE for triples extraction. Google search and Wikipedia are our main sources to get the text related to specified entities …

RDF triples extraction from company web pages: comparison of state-of-the-art Deep Models
W Baes, F Portet, H Mirisaee… – … Deep Learning meets …, 2020 – hal.archives-ouvertes.fr
Relation extraction (RE) is a promising way to extend the semantic web from web pages. However, it is unclear how RE can deal with the several challenges of web pages such as noise, data sparsity and conflicting information. In this paper, we benchmark state-of-the-art …

Greenfields Gold Deposit Exploration Techniques using Conformal Geometric Algebra-Based Arsenopyrite Trace Element Assemblage Models
S Thiruvengadam, M Murphy, JS Tan… – Journal of Geochemical …, 2020 – Elsevier
… is computed with reference to Sect. 2.1. Each hyperfield is a multivector which is composed of unique graded elements with associated coefficients. The ‘tuple extraction operator’ (denoted as ‘? ???’), is defined as an operator which isolates the various coefficients …

Device Feature Extraction Based on Parallel Neural Network Training for Replay Spoofing Detection
CH You, J Yang – IEEE/ACM Transactions on Audio, Speech …, 2020 – ieeexplore.ieee.org
… corre- sponding genuine speech. We start our proposed RDF extraction from the analysis of the device system, then we introduce the training of the neural network, finally the RDF extractor is developed. A. Analysis of Replay …

Improving Natural Language Queries Search and Retrieval through Semantic Image Annotation Understanding
H Samih, S Rady, M Ismail, T Gharib – International Journal of …, 2021 – journals.ekb.eg
… Manual triples extraction … The results show that the proposed semantic understanding extracts about 97% of the Attributes and instance relations, 94% for the semantic relations and 100% for the multiword dependence relations compared to the manual triples extraction …

Open Entity Semantic Relation Extraction in Big Data Environment
L Zhen, Y Zengchun – 2020 International Conference on Cyber …, 2020 – ieeexplore.ieee.org
… The traditional method extracts the relation triple according to the position relation of the entity pair and the relation indicator word in the sentence, this method will bring noise. A tuple extraction algorithm based on syntactic tree is proposed to reduce noise …

Research on Open Entity Semantic Relation Extraction in Big Data Environment
L Zhen – 2020 International Conference on Cyber-Enabled …, 2020 – ieeexplore.ieee.org
… The traditional method extracts the relation triple according to the position relation of the entity pair and the relation indicator word in the sentence, this method will bring noise. A tuple extraction algorithm based on syntactic tree is proposed to reduce noise …

Syntactic and Semantic-driven Learning for Open Information Extraction
J Tang, Y Lu, H Lin, X Han, L Sun, X Xiao… – Proceedings of the 2020 …, 2020 – aclweb.org
… The motivation of our method is that, although tuple extraction is a hard task, its inverse problem – tuple assessment is easier to resolve by exploiting the syntactic regularities of relation expressions and the semantic consis- tency between a tuple and its original sentence …

OntoBestFit: A Best-Fit Occurrence Estimation strategy for RDF driven faceted semantic search
G Deepak, A Santhanavijayan – Computer Communications, 2020 – Elsevier
… Web thesauri. The objective of RDF extraction from the Semantic Wiki is to get various contextually related triplet structures from real-world knowledge to pave the way of catching all possible contexts of the query word. The RDF …

Device Feature Extraction Based on Parallel Neural Network Training for Replay Spoofing Detection
Y Changhuai, Y Jichen – 2020 – oar.a-star.edu.sg
… genuine speech. We start our proposed RDF extraction from the analysis of the device system, then we introduce the training of the neural network, finally the RDF extractor is developed. A. Analysis of Replay Device System This …

Initial Exploitation of Natural Language Processing Techniques on NATO Strategy and Policies
G Valiyev, M Piraino, A Kok, M Street, II Mestric… – Information & …, 2020 – it4sec.org
… The Open Information Extractor (Open IE) 16 is one of the Stanford CoreNLP modules able to extract the grammatical structure of sentences and identify the triples. Extraction of triples from sentences provide the possibility to determine the core aim/meaning of each sentence …

DPRL Systems in the CLEF 2020 ARQMath Lab
B Mansouri, DW Oard, R Zanibbi – … Notes of CLEF 2020-Conference and …, 2020 – dei.unipd.it
… please see the paper): – Tuple Extraction: Using Tangent-S, LATEX formulas are converted to Pre- sentation and Content MathML, from which the internal SLT and OPT formula representations are produced. Depth-first traversals …

Learning a Lightweight Representation: First Step Towards Automatic Detection of Multidimensional Relationships between Ideas
A Khiat – 2020 IEEE 14th International Conference on Semantic …, 2020 – ieeexplore.ieee.org
… we attempted to structure ideas automatically in a machine-readable way ie into triples: subject/predicate/object using Stanford OpenIE (Open Information Extraction) [6]. We found the same dif- ficulties as natural language processing in applying triples extraction on ideas, ie …

Relation Extraction Based on Relation Label Constraints
K Lin, K Miao, W Hong, C Yuan – 2020 IEEE 6th International …, 2020 – ieeexplore.ieee.org
… Relation extraction is a sub-task of information extraction, and also a step to building a large-scale knowledge graph such as DBpedia [11], Freebase [12] and Knowledge Vault [13]. Early work in relational triples extraction took a pipeline approach …

Chinese Explanatory Opinion Relationship Recognition Based on Improved Target Attention Mechanism
X Cao, C Zhu, C Lv – 2020 3rd International Conference on …, 2020 – ieeexplore.ieee.org
… The seven-tuple extraction results for this example are as follows: (Iphone 7, appearance design, very nice, 2, null, null, null) (Iphone 7, performance index, is all good, 2, null, null, null) (Iphone 7, runs, smoothly, 2, playing games and watching TV are not slow down, all aspects …

Extracting and Cleaning RDF Data
M Farid – 2020 – uwspace.uwaterloo.ca
… x Page 11. List of Figures 1.1 Architecture Overview of RDF Extraction and Cleaning … ? integrity constraints Automatic Curation Constraint Discovery author Clean RDF Data (1) Extraction (2) Cleaning Figure 1.1: Architecture Overview of RDF Extraction and Cleaning II …

Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network
T Jiang, T Zhao, B Qin, T Liu, NV Chawla… – arXiv preprint arXiv …, 2020 – arxiv.org
… We define a new tuple representation: Definition 1 (Open KB Relation Tuple) A (sentence, re- lation, subject, object)-tuple is used to describe the relation tuple extraction, denoted by (s, r, esubj,eobj), where s ? S,r ? R,esubj,eobj ? E. Here S, R, E denote the set of …

CIAO: An Optimization Framework for Client-Assisted Data Loading
C Ding, D Tang, X Liang, AJ Elmore… – arXiv preprint arXiv …, 2021 – arxiv.org
… Invisible loading [17] piggybacks the data loading process with MapReduce [18] jobs that analyze the raw data. Invisible loading leverages MapReduce jobs’ parsing and tuple extraction operations to incrementally load tuples into a database system …

Data augmentation techniques for the Video Question Answering task
A Falcon, O Lanz, G Serra – European Conference on Computer Vision, 2020 – Springer
… which try to tackle this opportunity by exploiting template-based models or generative approaches. Using a semantic tuple extraction pipeline, Mahendru et al. [22] extract from each question a premise, ie a tuple made of either …

Probabilistic Topic Models for Enriching Ontology from Texts
A Tissaoui, S Sassi, R Chbeir – SN Computer Science, 2020 – Springer
… The authors build a gazetteer based on WordNet, where concepts in COSCHKR are matched to their synonyms. After that, they perform triples extraction in terms of relations and concepts. Finally, they associate the triples with the ontology and then perform property matching …

Knowledge Graph-based Event Embedding Framework for Financial Quantitative Investments
D Cheng, F Yang, X Wang, Y Zhang… – Proceedings of the 43rd …, 2020 – dl.acm.org
… The model includes three parts: 1) Multi-source input layer, which transfers the raw texts into event tuples, relation tuples and the subsequent knowl- edge graph. In particular, we employ the widely-used OpenIE v5.13 for event tuple extraction [35] …

Open Information Extraction for Knowledge Graph Construction
I Muhammad, A Kearney, C Gamble, F Coenen… – … on Database and Expert …, 2020 – Springer
… One of the first few attempts at creating a knowledge graph in the biomedical science domain involved the use of rdf-extraction from excel sheets in [20]. A recent, frequently cited work [21] focused on the construction of a knowledge graph for the domain of biomedical sciences …

Open Information Extraction for Knowledge Graph Construction
P Williamson – Database and Expert Systems Applications: DEXA …, 2020 – books.google.com
… One of the first few attempts at creating a knowledge graph in the biomedical science domain involved the use of rdf-extraction from excel sheets in [20]. A recent, frequently cited work [21] focused on the construction of a knowledge graph for the domain of biomedical sciences …

Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers
S Montella, B Fabre, T Urvoy, J Heinecke… – arXiv preprint arXiv …, 2020 – arxiv.org
… After this first selection, 57 million (unique) sentences remain. Henceforth, we coin this set of sentences WS1. 4.2.2 Triple Extraction Triples extraction is challenging and non-trivial, demanding a sharp understanding of linguistic structure …

Identifying security issues for mobile applications based on user review summarization
C Tao, H Guo, Z Huang – Information and Software Technology, 2020 – Elsevier
… (3) Security-related review sentence extraction based on keywords; (4) triples extraction from security-related review sentences based on semantic patterns; (5) Visualization of summarization with radar charts and corresponding review instances …

Neural Networks for Detecting Irrelevant Questions During Visual Question Answering
M Li, C Weber, S Wermter – International Conference on Artificial Neural …, 2020 – Springer
… The QRPE dataset is curated automatically based on the MSCOCO [14], Visual Genome [13] and VQA v2 dataset [7]. First-order and second-order premises are firstly extracted from questions through a semantic tuple extraction pipeline used in the SPICE metric [1] for …

Joint Extraction of Entities and Relations Based on Hierarchical Sequence Labeling
J Tian, X Lü, X You, G Xiao, J Han – Beijing Da Xue Xue Bao, 2021 – search.proquest.com
… ? 2 ????????? Fig. 2 Label design of object and relationship Page 4. ??????(?????) ? 57 ? ? 1 ? 2021 ? 1 ? 56 ? 3 ????????????? Fig. 3 Structure diagram of entity relationship triples extraction model …

NSTM: Real-Time Query-Driven News Overview Composition at Bloomberg
J Bambrick, M Xu, A Almonte, I Malioutov… – arXiv preprint arXiv …, 2020 – arxiv.org
… then scored by a ranker. 4.4.1 OpenIE-based Tuple Extraction Open Domain Information Extraction (OpenIE) presents an unsupervised approach to extract sum- mary candidates from an input sentence. First, we construct a …

Rule-enhanced Noisy Knowledge Graph Embedding via Low-quality Error Detection
Y Hong, C Bu, T Jiang – 2020 IEEE International Conference on …, 2020 – ieeexplore.ieee.org
… This kind of noise is what we call the entity type error. For instance, given the triple (LiBai, IsMarriedTo, Shandong), this entity type noise triple is generated by the current knowledge triples extraction method [37] with the real-life noisy text …

Construction of a Cloud Scenario Knowledge Graph for Cloud Service Market
S Zhang, X Liu, B Xu, L Cai, Y Hu – 2020 IEEE 11th …, 2020 – ieeexplore.ieee.org
… Figure 8. The format of training data 505 Page 4. V. RESULTS A. Triples Extraction We adopted rule-based method to extract entities from cloud service websites, including cloud service entities, cloud application scenario entities, cloud services customer entities and properties …

UNaProd: A Universal Natural Product Database for Materia Medica of Iranian Traditional Medicine
A Naghizadeh, D Hamzeheian, S Akbari… – Evidence-Based …, 2020 – hindawi.com
Journals; Publish with us; Publishing partnerships; About us; Blog. Evidence-Based Complementary and Alternative Medicine. +Journal Menu. PDF. Journal overview. For authorsFor reviewersFor editorsTable of Contents Special Issues.

Information mining and similarity computation for semi-/un-structured sentences from the social data
P Zhang, X Huang, L Zhang – Digital Communications and Networks, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Simultaneously linking entities and extracting relations from biomedical text without mention-level supervision
T Bansal, P Verga, N Choudhary… – Proceedings of the AAAI …, 2020 – ojs.aaai.org
… prediction task on the development set of CTD. For this, we consider perfect accuracy on relation prediction, so the recall on tuple extraction is limited only by the entity linking accuracy. We consider three methods for entity linking …

Extracting and Evaluating Personal Interests with Dialogue Agent
Y Tokuda, S Nakatani, S Saiki, M Nakamura… – … Conference on Human …, 2020 – Springer
In order to realize a continuous conversation between a dialog agent and a user, it is important to generate topics that are close to the user. In this paper, we propose a method for extracting and…

Towards medical knowmetrics: representing and computing medical knowledge using semantic predications as the knowledge unit and the uncertainty as the …
X Li, S Peng, J Du – Scientometrics, 2021 – Springer
In China, Prof. Hongzhou Zhao and Zeyuan Liu are the pioneers of the concept “knowledge unit” and “knowmetrics” for measuring knowl.

Joint Extraction of Entity and Relation Based on Pre-trained Language Model
M Zhu, J Xue, G Zhou – 2020 12th International Conference on …, 2020 – ieeexplore.ieee.org
… model to extract entities and relations. It solves the problem of overlapping triples extraction by combining the multi-layer tagging scheme, subject extractor, and predicate-object extractor. Specifically, we use the subject extractor …

Experimental evidence extraction system in data science with hybrid table features and ensemble learning
W Yu, W Peng, Y Shu, Q Zeng, M Jiang – Proceedings of The Web …, 2020 – dl.acm.org
Page 1. Experimental Evidence Extraction System in Data Science with Hybrid Table Features and Ensemble Learning Wenhao Yu 1 , Wei Peng1,2, Yu Shu1,3, Qingkai Zeng 1 , Meng Jiang 1 1Department of Computer Science …

Open Information Extraction as Additional Source for Kazakh Ontology Generation
N Khairova, S Petrasova, O Mamyrbayev… – Asian Conference on …, 2020 – Springer
… Language. Size, words. Precision. Agreement. Kazakh. 225 000. 71.0%. 0.72. 5 Conclusions and Future Works. The main result of this research is the adaptation of the developed logical-linguistic model for fact triples extraction from unstructured Kazakh texts …

Measuring Information Propagation in Literary Social Networks
M Sims, D Bamman – arXiv preprint arXiv:2004.13980, 2020 – arxiv.org
… in terms of their narrative functions). 4.1 Results In order to test implicit information propagation in literature, we run tuple extraction on 5,269 works of fiction from the Project Gutenberg corpus. We find that roughly 3,600 of these …

Wastes to be the source of nutrients and energy to mitigate climate change and ensure future sustainability: options and strategies
M Ahmed, S Ahmad, M Tariq, Z Fatima… – Journal of Plant …, 2020 – Taylor & Francis
… In the first type, organic fraction is separated and stabilized through biological means, while RDF and recyclable fraction is recovered from residue. In the second type, the compost is dried and followed by RDF extraction (Bilitewski, Oros, and Christensen 2011) …

Modeling Preconditions in Text with a Crowd-sourced Dataset
H Kwon, M Koupaee, P Singh, G Sawhney… – arXiv preprint arXiv …, 2020 – arxiv.org
… additional gain (+1.5 points). Further inspection of the tuple- based representation shows that automatic tuple extraction sometimes introduces errors and misses critical context and other important discourse cues. The best results …

Real-Time Semantic Web Data Stream Processing Using Storm
M Banane – 2020 International Conference on Computing and …, 2020 – ieeexplore.ieee.org
… Tech. rep., W3C. (2004) [2] Gerber D., Hellmann S., Buhmann L., Soru T., Usbeck R., Ngonga Ngomo AC. (2013) Real-Time RDF Extraction from Unstructured Data Streams. In: Alani H. et al. (eds) The Semantic Web – ISWC 2013. ISWC 2013 …

Link Prediction using Numerical Weights for Knowledge Graph Completion within the Scholarly Domain
M Nayyeri, GM Cil, S Vahdati, F Osborne… – 2020 – openreview.net
Page 1. Link Prediction using Numerical Weights for Knowledge Graph Completion within the Scholarly Domain Mojtaba Nayyeri1, Gökce Müge C¸il1, Sahar Vahdati2, Francesco Osborne5, Andrey Kravchenko3, Simone Angioni6 …

Summarizing Unstructured Logs in Online Services
W Meng, F Zaiter, Y Huang, Y Liu, S Zhang… – arXiv preprint arXiv …, 2020 – arxiv.org
… The process of building it can be divided into three parts: obtaining the logs data from different services; extracting and improving templates used to assist the triples extraction; and manual annotation. We sourced the logs from different types of systems and services …

An Approach for Improving DBpedia as a Research Data Hub
JGN Ngomo, GR Lopes, MLM Campos… – Proceedings of the …, 2020 – dl.acm.org
… Each published article will result in a DBpedia RDF resource and corresponding triples. However, to keep our approach faithful to the original extraction, DBpedia remains responsible for resources and triples extraction from articles published by our approach …

A collective entity linking algorithm with parallel computing on large-scale knowledge base
Y Xia, X Wang, L Gu, Q Gao, J Jiao, C Wang – The Journal of …, 2020 – Springer
Entity linking is a central concern of automatic knowledge question answering and knowledge base population. Traditional collective entity linking approach.

Enhancing Online Knowledge Graph Population with Semantic Knowledge
D Fernàndez-Cañellas, JM Rimmek… – International Semantic …, 2020 – Springer
Knowledge Graphs (KG) are becoming essential to organize, represent and store the world’s knowledge, but they still rely heavily on humanly- curated structured data. Information Extraction (IE) tasks,…

Metaknowledge Extraction Based on Multi-Modal Documents
S Liu, R Xu, B Geng, Q Sun, L Duan, Y Liu – arXiv preprint arXiv …, 2021 – arxiv.org
Page 1. PREPRINT VERSION ON ARXIV 1 Metaknowledge Extraction Based on Multi-Modal Documents Shukan Liu?, Ruilin Xu?, Boying Geng†, Qiao Sun, Li Duan, and Yiming Liu Abstract—The triple-based knowledge in …

Ranking semantic web services by matching triples and query based on similarity measure
M Santhoshkumar, S Sagayaraj – International Journal of Information …, 2020 – Springer
A Web Service (WS) provides interoperability among platforms. To find out a desired web service that matches the user requirements are difficult, which rai.

Precise temporal slot filling via truth finding with data-driven commonsense
X Wang, M Jiang – Knowledge and Information Systems, 2020 – Springer
The task of temporal slot filling (TSF) is to extract values of specific attributes for a given entity, called “facts”, as well as temporal tag.

Towards Scalable Network Traffic Measurement With Sketches
R Jang – 2020 – stars.library.ucf.edu
Page 1. University of Central Florida STARS Electronic Theses and Dissertations, 2020- 2020 Towards Scalable Network Traffic Measurement With Sketches Rhongho Jang University of Central Florida Part of the OS and Networks …

Better together: an ensemble learner for combining the results of ready-made entity linking systems
RS João, P Fafalios, S Dietze – Proceedings of the 35th Annual ACM …, 2020 – dl.acm.org
Page 1. Better Together – An Ensemble Learner for Combining the Results of Ready-made Entity Linking Systems Renato Stoffalette João L3S Research Center, Leibniz University of Hannover Hannover, Germany joao@L3S.de …

Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
L Orr, M Leszczynski, S Arora, S Wu, N Guha… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation Laurel Orr†, Megan Leszczynski†, Simran Arora†, Sen Wu†, Neel Guha†, Xiao Ling‡, and Christopher Ré† †Stanford University ‡Apple …

Mining information from sentences through Semantic Web data and Information Extraction tasks
JL Martinez-Rodriguez… – Journal of …, 2020 – journals.sagepub.com
The Semantic Web provides guidelines for the representation of information about real-world objects (entities) and their relations (properties). This is helpful for the dissemination and consumptio…

Approximate partition selection for big-data workloads using summary statistics
K Rong, Y Lu, P Bailis, S Kandula, P Levis – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Approximate Partition Selection for Big-Data Workloads using Summary Statistics Kexin Rong†?, Yao Lu†, Peter Bailis?, Srikanth Kandula†, Philip Levis? Microsoft†, Stanford? ABSTRACT Many big-data clusters store …

SPRINT: Semantics for PerfoRmant and scalable INteroperability of multimodal Transport
M Sadeghi, P Buchní?ek, A Carenini… – … Research Arena TRA …, 2020 – re.public.polimi.it
… block. At the end of Source message to RDF unmarshalling Graph enrichment with additional RDF data Ontology loading Additional transformation rules RDF extraction and marshalling to the destination format Page 9. Sadeghi …

A game-based framework for crowdsourced data labeling
J Yang, J Fan, Z Wei, G Li, T Liu, X Du – The VLDB Journal, 2020 – Springer
… 3.2 Formalization of minimax objective For illustration purpose, Example 2 shows an extreme case that one counterexample is enough to refute all rules covering the tuple … Fig. 5 Candidate rules construction extraction (RE) …

An algorithmic approach to rank the disambiguous entities in Twitter streams for effective semantic search operations
NS Kumar, M Dinakaran – S?dhan?, 2020 – Springer
The most challenging task in any modern reasoning system is that it has been completely relied on automatic knowledge acquisition from the unstructured tex.

Identifying Subjects of Online Opinion from Public Health Emergencies
S Qi, M Dongmei, W Ping… – Data Analysis and …, 2020 – manu44.magtech.com.cn
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Aspects of Semantic ETL
RP Nath – 2020 – vbn.aau.dk
Page 1. Aalborg Universitet Aspects of Semantic ETL Nath, Rudra Pratap Publication date: 2020 Document Version Publisher’s PDF, also known as Version of record Link to publication from Aalborg University Citation for published version (APA): Nath, RP (2020) …

Aspects of semantic ETL
RP Deb Nath – 2020 – upcommons.upc.edu
Page 1. T BI I DC Aspects of Semantic ETL Ph.D. Dissertation Rudra Pratap Deb Nath Dissertation submitted June, 2020 A thesis submitted to the Technical Faculty of IT and Design at Aalborg Uni- versity (AAU) and the Department …

The CENDARI Infrastructure
MK Fekete, J Lehmann, D Stuart, C Thiel – hal.inria.fr
… Admins Front Office OAI-?PMH Providers E lasti c PgSQL A MySQ L PgSQL B Solr Re d is B Pro2 Pro1 Back Office Re d is A API NERD RDF extraction Docs Document Dispatcher E lasti c Se arch Data Backup Ontology Uploader serves Ontology Viewer IIP im age V irtu o so …

Supporting domain modeling with automated knowledge acquisition and modeling recommendations
H Agt-Rickauer – 2020 – depositonce.tu-berlin.de
Page 1. Supporting Domain Modeling with Automated Knowledge Acquisition and Modeling Recommendations vorgelegt von Diplom-Informatiker (FH) Henning Agt-Rickauer, geb. Agt Von der Fakultät IV – Elektrotechnik und …