Relation Extraction 2014

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100 Best GitHub: Relation ExtractionRelation Extraction & Dialog Systems | Relation Extraction 2015

Typed tensor decomposition of knowledge bases for relation extraction KW Chang, W Yih, B Yang… – Proceedings of the 2014 …, 2014 – Abstract While relation extraction has traditionally been viewed as a task relying solely on textual data, recent work has shown that by taking as input existing facts in the form of entity- relation triples from both knowledge bases and textual data, the performance of relation … Cited by 19 Related articles All 15 versions

Distant supervision for relation extraction with matrix completion M Fan, D Zhao, Q Zhou, Z Liu… – Proceedings of the …, 2014 – Abstract The essence of distantly supervised relation extraction is that it is an incomplete multi-label classification problem with sparse and noisy features. To tackle the sparsity and noise challenges, we propose solving the classification problem using matrix completion … Cited by 11 Related articles All 8 versions

Combining distant and partial supervision for relation extraction G Angeli, J Tibshirani, JY Wu… – Proceedings of the 2014 …, 2014 – … October 28, 2014 3 / 19 Page 7. Relation Extraction Input: Sentences containing (entity, slot value). Output: Relation between entity and slot value. … Page 8. Relation Extraction Input: Sentences containing (entity, slot value). Output: Relation between entity and slot value. … Cited by 11 Related articles All 10 versions

Employing word representations and regularization for domain adaptation of relation extraction TH Nguyen, R Grishman – … of the 52nd Annual Meeting of the …, 2014 – Abstract Relation extraction suffers from a performance loss when a model is applied to out- of-domain data. This has fostered the development of domain adaptation techniques for relation extraction. This paper evaluates word embeddings and clustering on adapting … Cited by 7 Related articles All 9 versions

Relation extraction from the web using distant supervision I Augenstein, D Maynard, F Ciravegna – Knowledge Engineering and …, 2014 – Springer Abstract Extracting information from Web pages requires the ability to work at Web scale in terms of the number of documents, the number of domains and domain complexity. Recent approaches have used existing knowledge bases to learn to extract information with … Cited by 7 Related articles All 6 versions

Chinese open relation extraction for knowledge acquisition YH Tseng, LH Lee, SY Lin, BS Liao, MJ Liu… – EACL …, 2014 – Abstract This study presents the Chinese Open Relation Extraction (CORE) system that is able to extract entity-relation triples from Chinese free texts based on a series of NLP techniques, ie, word segmentation, POS tagging, syntactic parsing, and extraction rules. … Cited by 6 Related articles All 7 versions

Infusion of labeled data into distant supervision for relation extraction M Pershina, B Min, W Xu, R Grishman – Proceedings of ACL, 2014 – Abstract Distant supervision usually utilizes only unlabeled data and existing knowledge bases to learn relation extraction models. However, in some cases a small amount of human labeled data is available. In this paper, we demonstrate how a state-of-theart multi- … Cited by 4 Related articles All 7 versions

Seed Selection for Distantly Supervised Web-Based Relation Extraction I Augenstein – Proceedings of SWAIE, 2014 – Abstract In this paper we consider the problem of distant supervision to extract relations (eg origin (musical artist, location)) for entities (eg ‘The Beatles’) of certain classes (eg musical artist) from Web pages by using background information from the Linking Open Data cloud … Cited by 5 Related articles All 5 versions

Self-supervised relation extraction using UMLS R Roller, M Stevenson – Information Access Evaluation. Multilinguality, …, 2014 – Springer Abstract Self-supervised relation extraction uses a knowledge base to automatically annotate a training corpus which is then used to train a classifier. This approach has been successfully applied to different domains using a range of knowledge bases. This paper … Cited by 5 Related articles All 3 versions

Medical relation extraction with manifold models C Wang, J Fan – Proceedings of the 52nd Annual Meeting of …, 2014 – Abstract In this paper, we present a manifold model for medical relation extraction. Our model is built upon a medical corpus containing 80M sentences (11 gigabyte text) and designed to accurately and efficiently detect the key medical relations that can facilitate … Cited by 4 Related articles All 5 versions

Information and Relation Extraction for Semantic Annotation of eBook Texts A Uddin, R Piryani, VK Singh – Recent Advances in Intelligent Informatics, 2014 – Springer Abstract This paper presents our algorithmic approach for information and relation extraction from unstructured texts (such as from eBook sections or webpages), performing other useful analytics on the text, and automatically generating a semantically meaningful structure ( … Cited by 3 Related articles All 3 versions

An intensive case study on kernel-based relation extraction SP Choi, S Lee, H Jung, S Song – Multimedia Tools and Applications, 2014 – Springer Abstract Relation extraction refers to a method of efficiently detecting and identifying predefined semantic relationships within a set of entities in text documents. Numerous relation extractionfc techniques have been developed thus far, owing to their innate … Cited by 3 Related articles All 4 versions

REEL: A relation extraction learning framework P Barrio, G Simões, H Galhardas… – … of the 14th ACM/IEEE-CS …, 2014 – Abstract We introduce the REEL (RElation Extraction Learning) framework, an open source framework that facilitates the development and evaluation of relation extraction systems over text collections. To define a relation extraction system for a new relation and text collection … Cited by 2 Related articles All 14 versions

Application-Driven Relation Extraction with Limited Distant Supervision A Vlachos, S Clark – COLING 2014, 2014 – Abstract Recent approaches to relation extraction following the distant supervision paradigm have focused on exploiting large knowledge bases, from which they extract substantial amount of supervision. However, for many relations in real-world applications, there are … Cited by 3 Related articles All 8 versions

Omni-word Feature and Soft Constraint for Chinese Relation Extraction Y Chen, Q Zheng, W Zhang – Proceedings of the 52nd Annual Meeting …, 2014 – Abstract Chinese is an ancient hieroglyphic. It is inattentive to structure. Therefore, segmenting and parsing Chinese are more difficult and less accurate. In this paper, we propose an Omniword feature and a soft constraint method for Chinese relation extraction. … Cited by 4 Related articles All 7 versions

Assessing the role of a medication-indication resource in the treatment relation extraction from clinical text CA Bejan, WQ Wei, JC Denny – Journal of the American …, 2014 – Objective To evaluate the contribution of the MEDication Indication (MEDI) resource and SemRep for identifying treatment relations in clinical text. Materials and methods We first processed clinical documents with SemRep to extract the Unified Medical Language … Cited by 2 Related articles All 4 versions

Cross-lingual annotation projection for weakly-supervised relation extraction S Kim, M Jeong, J Lee, GG Lee – ACM Transactions on Asian Language …, 2014 – Abstract Although researchers have conducted extensive studies on relation extraction in the last decade, statistical systems based on supervised learning are still limited, because they require large amounts of training data to achieve high performance level. In this … Cited by 2 Related articles

CoRE: a context-aware relation extraction method for relation completion Z Li, M Sharaf, L Sitbon, X Du… – Knowledge and Data …, 2014 – Abstract—We identify Relation Completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation R, RC attempts at linking entity pairs between two … Cited by 3 Related articles All 7 versions

Grounded Feature Selection for Biomedical Relation Extraction by the Combinative Approach SJ Song, GE Heo, HJ Kim, HJ Jung, YH Kim… – Proceedings of the ACM …, 2014 – Abstract Relation extraction is an important task in biomedical areas such as protein-protein interaction, gene-disease interactions, and drug-disease interactions. In recent years, it has been widely researched to automatically extract biomedical relations in a vest amount of … Cited by 2 Related articles

A Pattern-Based Approach to Semantic Relation Extraction Using a Seed Ontology M Al-Yahya, L Aldhubayi… – … Computing (ICSC), 2014 …, 2014 – Abstract—This paper presents our experiment on the “Badea” system. A system designed for the automated extraction of semantic relations from text using a seed ontology and a pattern based approach. We describe the experiment using a set of Arabic language corpora for … Cited by 1 Related articles All 4 versions

Domain-adaptive relation extraction for the semantic web F Xu, H Uszkoreit, H Li, P Adolphs, X Cheng – Towards the Internet of …, 2014 – Springer Abstract In the THESEUS Alexandria use case, information extraction (IE) has been intensively applied to extract facts automatically from unstructured documents, such as Wikipedia and online news, in order to construct ontology-based knowledge databases for … Cited by 2 Related articles All 3 versions

Unsupervised Parsing for Generating Surface-Based Relation Extraction Patterns J Illig, W Allee, B Roth, D Klakow – EACL 2014, 2014 – Abstract Finding the right features and patterns for identifying relations in natural language is one of the most pressing research questions for relation extraction. In this paper, we compare patterns based on supervised and unsupervised syntactic parsing and present a … Cited by 2 Related articles All 7 versions

Information Extraction from German Patient Records via Hybrid Parsing and Relation Extraction Strategies HU Krieger, C Spurk, H Uszkoreit, F Xu… – Proceedings of the 9th …, 2014 – Abstract In this paper, we report on first attempts and findings to analyzing German patient records, using a hybrid parsing architecture and a combination of two relation extraction strategies. On a practical level, we are interested in the extraction of concepts and … Cited by 1 Related articles

A bottom-up kernel of pattern learning for relation extraction C Zhang, W Xu, S Gao, J Guo – Chinese Spoken Language …, 2014 – Abstract Measuring the similarity of patterns is the key in pattern-based approaches in relation extraction. Most existing methods generally rely on inflexible pattern similarity measurements which often lead to low recall. In this work, a novel kernel-based model is … Cited by 3 Related articles

Semantic Consistency: A Local Subspace Based Method for Distant Supervised Relation Extraction X Han, L Sun – Proceedings of ACL-14, 52nd Annual Meeting …, 2014 – Abstract One fundamental problem of distant supervision is the noisy training corpus problem. In this paper, we propose a new distant supervision method, called Semantic Consistency, which can identify reliable instances from noisy instances by inspecting … Cited by 1 Related articles All 7 versions

Insight to hyponymy lexical relation extraction in the patent genre versus other text genres L Andersson, M Lupu, J Palotti, F Piroi… – … Workshop on Patent …, 2014 – ABSTRACT Due to the large amount of available patent data, it is no longer feasible for industry actors to manually create their own terminology lists and ontologies. Furthermore, domain specific thesauruses are rarely accessible to the research community. In this … Cited by 1 Related articles All 2 versions

A convex relaxation for weakly supervised relation extraction E Grave – Conference on Empirical Methods in Natural …, 2014 – Abstract A promising approach to relation extraction, called weak or distant supervision, exploits an existing database of facts as training data, by aligning it to an unlabeled collection of text documents. Using this approach, the task of relation extraction can easily … Cited by 2 Related articles All 8 versions

Exploratory relation extraction in large text corpora A Akbik, T Michael, C Boden – International Conference on …, 2014 – Abstract In this paper, we propose and demonstrate Exploratory Relation Extraction (ERE), a novel approach to identifying and extracting relations from large text corpora based on user- driven and data-guided incremental exploration. We draw upon ideas from the information … Cited by 3 Related articles All 5 versions

Unsupervised Relation Extraction of In-Domain Data from Focused Crawls S Remus – Proceedings of the Student Research Workshop at the …, 2014 – Abstract This thesis proposal approaches unsupervised relation extraction from web data, which is collected by crawling only those parts of the web that are from the same domain as a relatively small reference corpus. The first part of this proposal is concerned with the … Cited by 2 Related articles All 6 versions

Modeling joint entity and relation extraction with table representation M Miwa, Y Sasaki – Proceedings of the 2014 Conference on Empirical …, 2014 – Abstract This paper proposes a history-based structured learning approach that jointly extracts entities and relations in a sentence. We introduce a novel simple and flexible table representation of entities and relations. We investigate several feature settings, search … Cited by 1 Related articles All 6 versions

Encoding Relation Requirements for Relation Extraction via Joint Inference L Chen, Y Feng, S Huang, Y Qin… – Proc. the 52nd Annual …, 2014 – Abstract Most existing relation extraction models make predictions for each entity pair locally and individually, while ignoring implicit global clues available in the knowledge base, sometimes leading to conflicts among local predictions from different entity pairs. In this … Cited by 2 Related articles All 5 versions

An Unsupervised Text Mining Method for Relation Extraction from Biomedical Literature C Quan, M Wang, F Ren – 2014 – Abstract The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence … Cited by 5 Related articles All 12 versions

Parse reranking for domain-adaptative relation extraction F Xu, H Li, Y Zhang, H Uszkoreit… – Journal of Logic and …, 2014 – Oxford Univ Press Abstract The article demonstrates how generic parsers in a minimally supervised information extraction framework can be adapted to a given task and domain for relation extraction (RE). For the experiments, two parsers that deliver n-best readings are included:(1) a generic … Cited by 1 Related articles All 4 versions

Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction M Wiegand, B Roth, D Klakow – Proc. of EACL, 2014 – Abstract We present a weakly-supervised induction method to assign semantic information to food items. We consider two tasks of categorizations being food-type classification and the distinction of whether a food item is composite or not. The categorizations are induced by … Cited by 2 Related articles All 7 versions

Annotation of computer science papers for semantic relation extraction Y Tateisi, Y Shidahara, Y Miyao… – Proceedings of the Nineth …, 2014 – Abstract We designed a new annotation scheme for formalising relation structures in research papers, through the investigation of computer science papers. The annotation scheme is based on the hypothesis that identifying the role of entities and events that are … Cited by 2 Related articles

Relation extraction for inferring access control rules from natural language artifacts J Slankas, X Xiao, L Williams, T Xie – Proceedings of the 30th Annual …, 2014 – Abstract With over forty years of use and refinement, access control, often in the form of access control rules (ACRs), continues to be a significant control mechanism for information security. However, ACRs are typically either buried within existing natural language (NL) … Cited by 1 Related articles All 3 versions

A Deep Learning Approach in Relation Extraction in EMRs J WU, Y GUAN, X LV – Intelligent Computer and Applications, 2014 – Electronic medical records contain huge quantity of medical knowledge, and it has great importance to the clinical decision support system. The relations of concepts and entities are very important in the medical knowledge and have significance in getting the relation of …

Distant Supervision for Relation Extraction Using Ontology Class Hierarchy-Based Features PHR Assis, MA Casanova – The Semantic Web: ESWC 2014 Satellite …, 2014 – Springer Abstract Relation extraction is a key step in the problem of structuring natural language text. This paper demonstrates a multi-class classifier for relation extraction, constructed using the distant supervision approach, along with resources of the Semantic Web. In particular, the … Related articles All 5 versions

Improving Open Relation Extraction via Sentence Re-Structuring J Schmidek, D Barbosa – Abstract Information Extraction is an important task in Natural Language Processing, consisting of finding a structured representation for the information expressed in natural language text. Two key steps in information extraction are identifying the entities … Cited by 1 Related articles All 2 versions

Freepal: A Large Collection of Deep Lexico-Syntactic Patterns for Relation Extraction J Kirschnick, A Akbik, H Hemsen – Abstract The increasing availability and maturity of both scalable computing architectures and deep syntactic parsers is opening up new possibilities for Relation Extraction (RE) on large corpora of natural language text. In this paper, we present FREEPAL, a resource … Related articles All 3 versions

Relation extraction with tree kernel for Indonesian sentences W Suwarningsih, I Supriana – ICT For Smart Society (ICISS), …, 2014 – Abstract—This paper propose of a study about kernels method for relation extraction in natural language tasks. Our study based on relation extraction using Indonesian parse tree kernel approach such as define subtree and subset tree, establish word dependency … Related articles All 2 versions

Kernel-based Methods for Relation Extraction Y Peng – 2014 – Page 1. Kernel-based Methods for Relation Extraction Yifan Peng Computer & Information Sciences University of Delaware Nov 3, 2014 Page 2. Outline 1 Relation extraction, classification, and kernel trick 2 Shallow linguistic methods 3 Tree kernels 4 Graph kernels … Related articles

Ontology-based Normalization for Disease-Lab test Relation Extraction Y Zhang, J Wang, C Tao, H Xu – Abstract—This poster describes our preliminary work on ontology-based normalization for diseases and lab tests, as a fundamental step toward disease-lab test relation extraction. Multiple ontologies are leveraged for this aim. Specifically, diseases and lab tests are first … Related articles

Creating a standard for evaluating Distant Supervision for Relation Extraction A Abad, A Moschitti – The First Italian Conference on Computational …, 2014 – Abstract English. This paper defines a standard for comparing relation extraction (RE) systems based on a Distant Supervision (DS). We integrate the well-known New York Time corpus with the more recent version of Freebase. Then, we define a simpler RE system … Related articles All 2 versions

Literature Survey in Natural Language Processing In the Sphere of Relation Extraction YV Haribhakta, B Chheda, N Agrawal, S Girme – ABSTRACT Today data is being produced at a phenomenal rate since our ability to store the data has been grown. Most of this available data is in unstructured form. Information extraction aims … Related articles All 3 versions

OCMiner: Text Processing, Annotation and Relation Extraction for the Life Sciences T Böhme, M Irmer, A Püschel, C Bobach, U Laube… – Abstract. We present OCMiner, a high-performance text processing system for large document collections of scientific publications. Several linguistic options allow adjusting the quality of annotation results which can be specialized and fine-tuned for the recognition of … Related articles

Relation Extraction Using TBL with Distant Supervision M Choi, H Kim – Abstract. Supervised machine learning methods have been widely used in relation extraction that finds the relation between two named entities in a sentence. However, their disadvantages are that constructing training data is a cost and time consuming job, and … Related articles All 3 versions

A Hybrid System for Temporal Relation Extraction from Discharge Summaries YL Yang, PT Lai, RTH Tsai – Technologies and Applications of Artificial …, 2014 – Springer Abstract Automatically detecting temporal relations among dates/times and events mentioned in patient records has much potential to help medical staff in understanding disease progression and patients response to treatments. It can also facilitate evidence- … Related articles All 3 versions

INDREX: In-database relation extraction T Kilias, A Löser, P Andritsos – Information Systems, 2014 – Elsevier Abstract The management of text data has a long-standing history in the human mankind. A particular common task is extracting relations from text. Typically, the user performs this task with two separate systems, a relation extraction system and an SQL-based query engine … Related articles

Noisy Or-based model for Relation Extraction using Distant Supervision A Nagesh, G Haffari, G Ramakrishnan – Abstract Distant supervision, a paradigm of relation extraction where training data is created by aligning facts in a database with a large unannotated corpus, is an attractive approach for training relation extractors. Various models are proposed in recent literature to align the … Cited by 2 Related articles All 7 versions

Semi-supervised Chinese Open Entity Relation Extraction M Wang, L Li, F Huang – Cloud Computing and Intelligence …, 2014 – Abstract: Open Information Extraction (IE) systems extract relational tuples from text, without requiring a pre-specified vocabulary, by identifying relation phrases and associated arguments in arbitrary sentences. A lot of work have been done for English Open IE, and …

Efficient Technique for Supervised Relation Extraction MP Sapate – Abstract: In information retrieval, information extraction is important that extracts the relation which exists between two entities. The different types of semantic relation exist between different entities. Information retrieval deals with the representation, access storage, … Related articles

Learning the Distinctive Pattern Space Features for Relation Extraction D Zeng, Y Chen, K Liu, J Zhao, X Lv – Chinese Computational Linguistics …, 2014 – Springer Abstract Recently, Distant Supervision (DS) is used to automatically generate training data for relation extraction. As the vast redundancy of information on the web, multiple sentences corresponding to a fact may be achieved. In this paper, we propose pattern space features … Related articles All 3 versions

Research on Pattern Representation Method in Semi-supervised Semantic Relation Extraction Based on Bootstrapping F Ye, H Shi, S Wu – Computational Intelligence and Design ( …, 2014 – Abstract—Semantic relation extraction is an important part of information extraction, it has application value in the automatic question answering system, retrieval system, ontology learning, semantic web annotation, and many other areas. Pattern representation method … Related articles

Unsupervised Relation Extraction M Mohanty, P Ruke, S Mathew, G Kulkarni… – Abstract:-World Wide Web consists of vast information which is scattered across millions of web pages. We consider the problem of extracting relations from this huge data. Relations can be unary such as, creating just lists of various cities, movies, actors, etc. or binary such … Related articles All 2 versions

An improved algorithm for relation extraction based on tri-training Z Zhong, FC Liu, Y Wu, N Jing – … Science, Electronics and …, 2014 – Abstract—The tri-training algorithm is an efficient co-training method for semi-supervised learning, and it has been used to extract semantic relation between entities in text. However, the tri-training method will introduce noises and lose some valuable samples while … Related articles All 2 versions

Pairwise Topic Model via relation extraction X Song, Y Shang, Y Ling, M Liu… – Big Data (Big Data), 2014 …, 2014 – ABSTRACT—Topic modeling is a powerful tool to model documents to find their underlying topics. However, the unstructured nature of the raw text makes it hard to model the semantic relationship between the text units, which may be the words, phrases or sentences, and … Related articles

Semantic relation extraction by Conditional Random Fields from Turkish Wikipedia pages C Girgin, B Diri – 2014 22nd Signal Processing and Communications …, 2014 – Relations between entities constitute the most important fundamental parts of semantic search technologies. The products that use semantic search technologies include datastores which keep relations between entities in their infrastructures. Various Relation … Related articles All 2 versions

Social relation extraction of large-scale logistics network based on mapreduce F Gui, F Zhang, Y Ma, M Liu… – Systems, Man and …, 2014 – Abstract—Social network is a social structure of nodes that are linked by various kinds of relationships, such as friends, web links, etc. To extract social relation based on logistics data will contribute significantly to detect some underlying crimes. One of the main … Related articles

Extraction of Relation Descriptors for Portuguese Using Conditional Random Fields S Collovini, L Pugens, AA Vanin, R Vieira – Advances in Artificial …, 2014 – Springer … Abstract. An important task in Information Extraction is Relation Extraction. Relation Extraction (RE) is the task of detecting and characterizing the semantic relations between entities in the text. This work proposes … Cited by 1 Related articles All 3 versions

Relation Extraction using Distant Supervision, SVMs, and Probabilistic First Order Logic MW Greaves – 2014 – We are drowning in information. In a fairly recent study, Hilbert and López (2011) estimated that humanity has stored a total of 295 exabytes (EB) of information. The growth of digital information is staggering: from an estimated 2.6 EB in 1986, to 15.8 EB in 1993, to 54.5 EB … Related articles All 4 versions

Trigger word mining for relation extraction based on activation force W Xu, C Zhang – International Journal of Communication …, 2014 – Wiley Online Library SUMMARY In this paper, relation extraction is characterized as structured feature learning, and activation force (AF) is employed to extract and construct structured features. Trigger word is a low-level feature, and it is very crucial in relation extraction. We define the trigger … Cited by 1 Related articles

A Hierarchical Model for Universal Schema Relation Extraction A Neelakantan, A Passos, A McCallum – Citeseer ABSTRACT Relation extraction by universal schema avoids mapping to a brittle, incomplete traditional schema by instead making predictions in the union of all input schemas, including textual patterns. Modeling these predictions by matrix competition with matrix factorization … Related articles All 2 versions

A Feature-Enriched Tree Kernel for Relation Extraction HD District – Abstract Tree kernel is an effective technique for relation extraction. However, the traditional syntactic tree representation is often too coarse or ambiguous to accurately capture the semantic relation information between two entities. In this paper, we propose a new tree … Related articles All 7 versions

Language Resources and Annotation Tools for Cross-Sentence Relation Extraction S Krause, H Li, F Xu, H Uszkoreit, R Hummel… – Proceedings of the …, 2014 – Abstract In this paper, we present a novel combination of two types of language resources dedicated to the detection of relevant relations (RE) such as events or facts across sentence boundaries. One of the two resources is the sar-graph, which aggregates for each target … Related articles All 2 versions

Evaluating open relation extraction over conversational texts M Imani – 2014 – In this thesis, for the first time the performance of Open IE systems on conversational data has been studied. Due to lack of test datasets in this domain, a method for creating the test dataset covering a wide range of conversational data has been proposed. Conversational … Related articles All 4 versions

Research of Conceptual Relation Extraction Based on Improved Hierar-chical Clustering Method C Xie, J Wu – Open Electrical & Electronic Engineering Journal, 2014 – Abstract: The main task of Ontology learning is concept extraction and conceptual relation extraction. This paper mainly studies the latter. Conceptual relation consists of taxonomic relation and non-taxonomic relation. It introduces hierarchy clustering method, and uses … Related articles All 2 versions

A bootstrapping and MV-RNN mixed method for relation extraction J Jianshu, C Guang, Z Chunyun – Network Infrastructure and …, 2014 – Abstract: The classical method for information extraction called bootstrapping is widely used for its good performance. But some inevitable weakness such as semantic drift and low recall hinders the improvement of the model. With the repopulation of neural network, … Related articles

A Hybrid Method for Chinese Entity Relation Extraction H Wang, Z Qi, H Hao, B Xu – Natural Language Processing and Chinese …, 2014 – Springer Abstract Entity relation extraction is an important task for information extraction, which refers to extracting the relation between two entities from input text. Previous researches usually converted this problem to a sequence labeling problem and used statistical models such … Related articles All 7 versions

A Survey and Exploration of Relation Extraction in Active Learning Systems A Lukic – Abstract The reliable recognition and extraction of semantic relations between entities is important to many applications in the domain of natural language processing and information retrieval, such as search engines and question-answering systems. In this … Related articles All 2 versions

Improving relation descriptor extraction with word embeddings and cluster features T Liu, M Li – Systems, Man and Cybernetics (SMC), 2014 IEEE …, 2014 – … Its typical subtasks include named entity recognition [3] and relation extraction [4]. Named entity recognition has been well-studied and it’s relatively matured [5], but relation extraction is more difficult and need to be paid more attention [6]. We will focus on relation extraction in … Related articles

A Problem-Action Relation Extraction Based on Causality Patterns of Clinical Events in Discharge Summaries JW Seol, SH Jo, W Yi, J Choi, KS Lee – Proceedings of the 23rd ACM …, 2014 – Abstract Medical knowledge extraction has great potential to improve the treatment quality of hospitals. In this paper, we propose a clinical problem-action relation extraction method. It is based on clinical semantic units and event causality patterns in order to present a … Related articles

Errata: Distant Supervision for Relation Extraction with Matrix Completion M Fan, D Zhao, Q Zhou, Z Liu, TF Zheng… – arXiv preprint arXiv: …, 2014 – Abstract: The essence of distantly supervised relation extraction is that it is an incomplete multi-label classification problem with sparse and noisy features. To tackle the sparsity and noise challenges, we propose solving the classification problem using matrix completion … Related articles All 2 versions

Wikipedia Taxonomic Relation Extraction using Wikipedia Distant Supervision H Shen, M Chen, R Bunescu, R Mihalcea – Ann Arbor – Abstract We present a relation extraction system that is specifically designed to extract taxonomic relations from Wikipedia. In contrast with previous related work, the proposed system does not rely on any external knowledge bases–its training examples and feature … Related articles All 2 versions

Distantly Supervised Web Relation Extraction for Knowledge Base Population I Augenstein, D Maynard, F Ciravegna – Abstract. Extracting information from Web pages for populating large, cross-domain knowledge bases requires methods which are suitable across domains, do not require manual effort to adapt to new domains, are able to deal with noise, and integrate … Related articles All 3 versions

A generalizable NLP framework for fast development of pattern-based biomedical relation extraction systems Y Peng, M Torii, CH Wu, K Vijay-Shanker – BMC bioinformatics, 2014 – Background Text mining is increasingly used in the biomedical domain because of its ability to automatically gather information from large amount of scientific articles. One important task in biomedical text mining is relation extraction, which aims to identify designated … Cited by 1 Related articles All 8 versions

Relation Extraction V Castelli, I Zitouni – Natural Language Processing of Semitic Languages, 2014 – Springer Abstract We discuss the problem of extracting semantic relations between entities from text. We concentrate on types of relations that belong to predefined classes, and we specifically address how to detect relations explicitly described in the text. We describe three main … Related articles All 3 versions

Automatic Multilabelling of Images and Semantic Relation Extraction G Santhosh Kumar – 2014 – In the recent years, there has been an explosive growth in the amount of visual data. Automatic Image Annotation (AIA) has been considered the state-of-the-art technique to annotate images with relevant keywords that enable efficient retrieval of these images. … Related articles All 2 versions

Natural language dependencies for ontological relation extraction MDS Seneviratne… – Advances in ICT for …, 2014 – Abstract—Natural Language Processing techniques play an essential role in extraction of necessary information for ontology construction from unstructured text. Identifying syntactic constituents and their dependencies in a sentence, boost the information extraction from … Related articles All 2 versions

Using Large Biomedical Databases as Gold Annotations for Automatic Relation Extraction T Ellendorff, F Rinaldi, S Clematide – Abstract We show how to use large biomedical databases in order to obtain a gold standard for training a machine learning system over a corpus of biomedical text. As an example we use the Comparative Toxicogenomics Database (CTD) and describe by means of a short … Related articles

Improvement of n-ary Relation Extraction by Adding Lexical Semantics to Distant-Supervision Rule Learning H Li, S Krause, F Xu, A Moro, H Uszkoreit, R Navigli – Abstract: A new method is proposed and evaluated that improves distantly supervised learning of pattern rules for n-ary relation extraction. The new method employs knowledge from a large lexical semantic repository to guide the discovery of patterns in parsed … Related articles

Motif-based Hyponym Relation Extraction from Wikipedia Hyperlinks B Wei, J Liu, J Ma, Q Zheng, W Zhang… – Knowledge and Data …, 2014 – Abstract—Discovering hyponym relations among domain-specific terms is a fundamental task in taxonomy learning and knowledge acquisition. However, the great diversity of various domain corpora and the lack of labeled training sets make this task very … Related articles All 6 versions

Transforming graph-based sentence representations to alleviate overfitting in relation extraction RJ Lima, J Batista, R Ferreira, F Freitas… – Proceedings of the …, 2014 – Abstract Relation extraction (RE) aims at finding the way entities, such as person, location, organization, date, etc., depend upon each other in a text document. Ontology Population, Automatic Summarization, and Question Answering are fields in which relation extraction … Related articles

Distant Supervision for Relation Extraction via Sparse Representation D Zeng, S Lai, X Wang, K Liu, J Zhao, X Lv – … Computational Linguistics and …, 2014 – Springer Abstract In relation extraction, distant supervision is proposed to automatically generate a large amount of labeled data. Distant supervision heuristically aligns the given knowledge base to free text and consider the alignment as labeled data. This procedure is effective to … Related articles All 3 versions

Efficient relation extraction method based on spatial feature using ELM H Liu, C Jiang, C Hu, L Zhang – Neural Computing and Applications – Springer Abstract Entity relation extraction can be applied in the automatic question answering system, digital library and many other fields. However, the previous works on this topic mainly focused on the features from a sentence itself in the data sets, without considering … Related articles

Relation extraction from biomedical literature with minimal supervision and grouping strategy M Liu, Y Ling, Y An, X Hu, A Yagoda… – … and Biomedicine (BIBM …, 2014 – Abstract—We develop a novel distant supervised model that integrates the results from open information extraction techniques to perform relation extraction task from biomedical literature. Unlike state-of-the-art models for relation extraction in biomedical domain which … Related articles All 3 versions

Relation Extraction for the Food Domain without Labeled Training Data–Is Distant Supervision the Best Solution? M Reiplinger, M Wiegand, D Klakow – Advances in Natural Language …, 2014 – Springer Abstract We examine the task of relation extraction in the food domain by employing distant supervision. We focus on the extraction of two relations that are not only relevant to product recommendation in the food domain, but that also have significance in other domains, … Related articles All 5 versions

Type-Aware Distantly Supervised Relation Extraction with Linked Arguments MKJGS Soderland, DS Weld – Abstract Distant supervision has become the leading method for training large-scale relation extractors, with nearly universal adoption in recent TAC knowledge-base population competitions. However, there are still many questions about the best way to learn such … Related articles All 8 versions

Towards Automatic Wayang Ontology Construction using Relation Extraction from Free Text HR Sanabila, R Manurung – EACL 2014, 2014 – Abstract This paper reports on our work to automatically construct and populate an ontology of wayang (Indonesian shadow puppet) mythology from free text using relation extraction and relation clustering. A reference ontology is used to evaluate the generated ontology. … Related articles All 6 versions

Senti-LSSVM: Sentiment-Oriented Multi-Relation Extraction with Latent Structural SVM L Qu, Y Zhang, R Wang, L Jiang… – Transactions of the …, 2014 – Abstract Extracting instances of sentiment-oriented relations from user-generated web documents is important for online marketing analysis. Unlike previous work, we formulate this extraction task as a structured prediction problem and design the corresponding … Related articles All 15 versions

Automatic semantic relation extraction from Portuguese texts LS Taba, H de Medeiros Caseli – Abstract Nowadays we are facing a growing demand for semantic knowledge in computational applications, particularly in Natural Language Processing (NLP). However, there aren’t sufficient human resources to produce that knowledge at the same rate of its … Related articles

Exploring Fine-grained Entity Type Constraints for Distantly Supervised Relation Extraction YLKLL Xu, J Zhao – Abstract Distantly supervised relation extraction, which can automatically generate training data by aligning facts in the existing knowledge bases to text, has gained much attention. Previous work used conjunction features with coarse entity types consisting of only four … Related articles All 5 versions

Robust Domain Adaptation for Relation Extraction via Clustering Consistency ML Nguyen, IW Tsang, KMA Chai, HL Chieu – Abstract We propose a two-phase framework to adapt existing relation extraction classifiers to extract relations for new target domains. We address two challenges: negative transfer when knowledge in source domains is used without considering the differences in relation … Cited by 1 Related articles All 6 versions

Review of Relation Extraction Methods: What Is New Out There? N Konstantinova – Analysis of Images, Social Networks and Texts, 2014 – Springer Abstract Relation extraction is a part of Information Extraction and an established task in Natural Language Processing. This paper presents an overview of the main directions of research and recent advances in the field. It reviews various techniques used for relation … Related articles All 3 versions

Biomedical Relation Extraction: From Binary to Complex D Zhou, D Zhong, Y He – Computational and mathematical methods in …, 2014 – Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are … Cited by 1 Related articles All 10 versions