We present a new method for detecting and disambiguating named entities in open domain text. A disambiguation SVM kernel is trained to exploit the high coverage and rich structure of the knowledge encoded in an online encyclopedia. The resulting model significantly outperforms a less informed baseline
Precisely identifying entities in web documents is essential for document indexing, web search and d...
To advance the Web of Linked Data, mapping ambiguous names in structured and unstructured contents o...
Named entity extraction and disambiguation have received much attention in recent years. Typical fie...
Semantic annotation of named entities for enriching unstructured content is a critical step in devel...
Abstract — Detecting entity mentions in a text and then map-ping them to their right entities in a g...
Named entity disambiguation is the task of disambiguating named entity mentions in natural language ...
Disambiguating named entities in natural language texts maps ambiguous names to canonical entities r...
In this project we designed and implemented a system based on the Learning To Rank framework to perf...
xii, 148 pages : color illustrations ; 30 cmPolyU Library Call No.: [THS] LG51 .H577P COMP 2014 XuNa...
One major problem in text mining and semantic retrieval is that detected entity mentions have to be ...
Over the last decades, several billion Web pages have been made available on the Web. The ongoing tr...
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entitie...
In this paper we present a novel disambiguation model, based on neural networks. Most existing studi...
Internet content has become one of the most important resources of information. Much of this informa...
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entitie...
Precisely identifying entities in web documents is essential for document indexing, web search and d...
To advance the Web of Linked Data, mapping ambiguous names in structured and unstructured contents o...
Named entity extraction and disambiguation have received much attention in recent years. Typical fie...
Semantic annotation of named entities for enriching unstructured content is a critical step in devel...
Abstract — Detecting entity mentions in a text and then map-ping them to their right entities in a g...
Named entity disambiguation is the task of disambiguating named entity mentions in natural language ...
Disambiguating named entities in natural language texts maps ambiguous names to canonical entities r...
In this project we designed and implemented a system based on the Learning To Rank framework to perf...
xii, 148 pages : color illustrations ; 30 cmPolyU Library Call No.: [THS] LG51 .H577P COMP 2014 XuNa...
One major problem in text mining and semantic retrieval is that detected entity mentions have to be ...
Over the last decades, several billion Web pages have been made available on the Web. The ongoing tr...
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entitie...
In this paper we present a novel disambiguation model, based on neural networks. Most existing studi...
Internet content has become one of the most important resources of information. Much of this informa...
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entitie...
Precisely identifying entities in web documents is essential for document indexing, web search and d...
To advance the Web of Linked Data, mapping ambiguous names in structured and unstructured contents o...
Named entity extraction and disambiguation have received much attention in recent years. Typical fie...