Is It Possible to Predict the Manual Web Accessibility Result Using the Automatic Result?

The most adequate approach for benchmarking web accessibility is manual expert evaluation supplemented by automatic analysis tools. But manual evaluation has a high cost and is impractical to be applied on large websites. In reality, there is no choice but to rely on automated tools when reviewing large web sites for accessibility. The question is: to what extent the results from automatic evaluation of a web site and individual web pages can be used as an approximation for manual results? This paper presents the initial results of an investigation aimed at answering this question. He have performed both manual and automatic evaluations of the accessibility of web pages of two sites and we have compared the results. In our data set automatically retrieved results could most definitely be used as an approximation manual evaluation results.

Automatic acquisition of Named Entities for Rule-Based Machine Translation

This paper proposes to enrich RBMTdictionaries with Named Entities(NEs) automatically acquired fromWikipedia. The method is appliedto the Apertium English-Spanishsystem and its performance comparedto that of Apertium with and withouthandtagged NEs. The system withautomatic NEs outperforms the onewithout NEs, while results vary whencompared to a system with handtaggedNEs (results are comparable forSpanish to English but slightly worstfor English to Spanish). Apart fromthat, adding automatic NEs contributesto decreasing the amount of unknownterms by more than 10%.