We describe a methodology for deriving content selection rules for NLG applications that aim to replace oral communications from human experts by written communications that are generated automatically. We argue for greater involvement of users and fo
Conventional terminology resources reach their limits when it comes to automatic content classificat...
Data-to-text systems are powerful in generating reports from data automatically and thus they simpli...
Natural language generation (NLG) technology is currently finding its way into commercial systems. P...
We describe a methodology for deriving content selection rules for NLG applications that aim to repl...
A Natural Language Generation system produces text using as input semantic data. One of its very fir...
A Natural Language Generation system produces text using as input semantic data. One of its very fir...
This chapter is about natural language texts generated automatically. We will discuss the motivation...
A standard architecture for an NLG system has<br />been defined in (Reiter and Dale, 2000). Their<br...
<F4.589e+05> Automatic natural language generation from underlying representations of informa...
Natural language generation (nlg) systems are computer software systems that pro-duce texts in Engli...
If an NLG system needs to be put in place as soon as possible it is not always possible to know in a...
Natural Language Generation (NLG) is defined as the systematic approach for producing human understa...
The automatic generation of natural language messages (or NLG) has been em-ployed in many computer s...
Natural Language Generation (NLG) is the process of generating natural language text from an input, ...
This paper outlines a number of ways in which defeasible rules can contribute to the content selecti...
Conventional terminology resources reach their limits when it comes to automatic content classificat...
Data-to-text systems are powerful in generating reports from data automatically and thus they simpli...
Natural language generation (NLG) technology is currently finding its way into commercial systems. P...
We describe a methodology for deriving content selection rules for NLG applications that aim to repl...
A Natural Language Generation system produces text using as input semantic data. One of its very fir...
A Natural Language Generation system produces text using as input semantic data. One of its very fir...
This chapter is about natural language texts generated automatically. We will discuss the motivation...
A standard architecture for an NLG system has<br />been defined in (Reiter and Dale, 2000). Their<br...
<F4.589e+05> Automatic natural language generation from underlying representations of informa...
Natural language generation (nlg) systems are computer software systems that pro-duce texts in Engli...
If an NLG system needs to be put in place as soon as possible it is not always possible to know in a...
Natural Language Generation (NLG) is defined as the systematic approach for producing human understa...
The automatic generation of natural language messages (or NLG) has been em-ployed in many computer s...
Natural Language Generation (NLG) is the process of generating natural language text from an input, ...
This paper outlines a number of ways in which defeasible rules can contribute to the content selecti...
Conventional terminology resources reach their limits when it comes to automatic content classificat...
Data-to-text systems are powerful in generating reports from data automatically and thus they simpli...
Natural language generation (NLG) technology is currently finding its way into commercial systems. P...