An End-to-End Entity Linking Approach for Tweets

نویسندگان

  • Ikuya Yamada
  • Hideaki Takeda
  • Yoshiyasu Takefuji
چکیده

We present a novel approach for detecting, classifying, and linking entities from Twitter posts (tweets). The task is challenging because of the noisy, short, and informal nature of tweets. Consequently, the proposed approach introduces several methods that robustly facilitate successful realization of the task with enhanced performance in several measures.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Entity Extraction, Linking, Classification, and Tagging for Social Media: A Wikipedia-Based Approach

Many applications that process social data, such as tweets, must extract entities from tweets (e.g., “Obama” and “Hawaii” in “Obama went to Hawaii”), link them to entities in a knowledge base (e.g., Wikipedia), classify tweets into a set of predefined topics, and assign descriptive tags to tweets. Few solutions exist today to solve these problems for social data, and they are limited in importa...

متن کامل

Making Sense of Microposts (#Microposts2015) Named Entity rEcognition & Linking Challenge

Microposts are small fragments of social media content and a popular medium for sharing facts, opinions and emotions. Collectively, they comprise a wealth of data that is increasing exponentially, and which therefore presents new challenges for the Information Extraction community, among others. This paper describes the Making Sense of Microposts (#Microposts2015) Workshop’s Named Entity rEcogn...

متن کامل

Knowledge-based Approach for Event Extraction from Arabic Tweets

Tweets provide a continuous update on current events. However, Tweets are short, personalized and noisy, thus raises more challenges for event extraction and representation. Extracting events out of Arabic tweets is a new research domain where few examples – if any – of previous work can be found. This paper describes a knowledge-based approach for fostering event extraction out of Arabic tweet...

متن کامل

Joint Recognition and Linking of Fine-Grained Locations from Tweets

Many users casually reveal their locations such as restaurants, landmarks, and shops in their tweets. Recognizing such fine-grained locations from tweets and then linking the location mentions to well-defined location profiles (e.g., with formal name, detailed address, and geo-coordinates etc.) offer a tremendous opportunity for many applications. Different from existing solutions which perform...

متن کامل

Kanopy4Tweets: Entity Extraction and Linking for Twitter

Named Entity rEcognition and Linking (NEEL) from text is an essential task in many Natural Language Processing (NLP) applications because it enables a better understanding of the content. However in the context of Social Media, NEEL is challenging due to the higher level of writing mistakes, fast language dynamics and often lack of context. To this end, we adapted Kanopy – an unsupervised graph...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015