Do you want to publish a course? Click here

AI Clerk Platform : Information Extraction DIY Platform

منظمة العفو الدولية كاتب منصة: منصة استخراج المعلومات

451   0   0   0.0 ( 0 )
 Publication date 2021
and research's language is English
 Created by Shamra Editor




Ask ChatGPT about the research

Information extraction is a core technology of natural language processing, which extracts some meaningful phrases/clauses from unstructured or semistructured content to a particular topic. It can be said to be the core technology of many language technologies and applications. This paper introduces AI Clerk Platform, which aims to accelerate and improve the entire process and convenience of the development of information extraction tools. AI Clerk Platform provides a friendly and intuitive visualized manual labeling interface, sets suitable semantic label in need, and implements, distributes and controls manual labeling tasks, so that users can complete customized information extraction models without programming and view the automatically predict results of models by three method. AI Clerk Platform further assists in the development of other natural language processing technologies and the derivation of application services.



References used
https://aclanthology.org/
rate research

Read More

إن الشبكات بأنواعها المختلفة بما فيها الشبكات المحلية الصغيرة يتوجب عليها تقديم الخدمة الجيدة للمستخدمين وهذا يحتاج إلى وجود نظام إدارة يتولى مهمة إدارة موارد الشبكة وخدماتها. الهدف من المشروع هو إعداد الخدمات بطريقة تسهل إدارة الشبكة على مدير النظ ام وتساعده على تنظيم العمل وتوفير الخدمات بأقل عبء وأقل اخطاء . حيث يساعدنا استخدام مخدم Zentyal في توفير الوقت والجهد لحل بعض الامور الروتينية وعبء الأخطاء الذي كان يظهر عند إعداد الخدمات بالطرق القديمة في نظام LINUX
The main objective of this research is to present a study on the design optimization of the 6-RUS Stewart platform. The geometric and kinematic models are calculated and the singular positions are determined, then its translation and orientation wor kspace are determining. The direct geometric model of the studied platform was determined by using a proposed hybrid method.
In this paper we introduce a vision towards establishing the Malta National Language Technology Platform; an ongoing effort that aims to provide a basis for enhancing Malta's official languages, namely Maltese and English, using Machine Translation. This will contribute towards the current niche of Language Technology support for the Maltese low-resource language, across multiple computational linguistics fields, such as speech processing, machine translation, text analysis, and multi-modal resources. The end goals are to remove language barriers, increase accessibility, foster cross-border services, and most importantly to facilitate the preservation of the Maltese language.
Natural Language Processing offers new insights into language data across almost all disciplines and domains, and allows us to corroborate and/or challenge existing knowledge. The primary hurdles to widening participation in and use of these new rese arch tools are, first, a lack of coding skills in students across K-16, and in the population at large, and second, a lack of knowledge of how NLP-methods can be used to answer questions of disciplinary interest outside of linguistics and/or computer science. To broaden participation in NLP and improve NLP-literacy, we introduced a new tool web-based tool called Natural Language Processing 4 All (NLP4All). The intended purpose of NLP4All is to help teachers facilitate learning with and about NLP, by providing easy-to-use interfaces to NLP-methods, data, and analyses, making it possible for non- and novice-programmers to learn NLP concepts interactively.
We present EMISSOR: a platform to capture multimodal interactions as recordings of episodic experiences with explicit referential interpretations that also yield an episodic Knowledge Graph (eKG). The platform stores streams of multiple modalities as parallel signals. Each signal is segmented and annotated independently with interpretation. Annotations are eventually mapped to explicit identities and relations in the eKG. As we ground signal segments from different modalities to the same instance representations, we also ground different modalities across each other. Unique to our eKG is that it accepts different interpretations across modalities, sources and experiences and supports reasoning over conflicting information and uncertainties that may result from multimodal experiences. EMISSOR can record and annotate experiments in virtual and real-world, combine data, evaluate system behavior and their performance for preset goals but also model the accumulation of knowledge and interpretations in the Knowledge Graph as a result of these episodic experiences.

suggested questions

comments
Fetching comments Fetching comments
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا