Catégorie : Building Bilbo

An idea, which naturally stuck us, is to try out learning a model with a complete proper noun feature set for each strategy. It will give us an objective upper bound on the annotation...

We extract seven different learning sets according to the defined strategies in the previous post. Several important fields are selected for the comparison including the surname, forename and place fields that are our main...

In the previous experiments on proper noun lists, certain author names were omitted because of parsing error. We deduce from this inadvertent mistake and the degradation of performance that we would have an improved...

Excluding any errors in manual annotation is hard to be achieved especially when the annotation structure is complex and data size is not small as ours. But the quality of manual annotation is one...

One of the main services that we have planed using automatic annotation is to provide a unique identifier such as DOI (Digital Object Identifier) to each reference. DOI is assigned by CrossRef, the registration...

First step to use the annotation result: Finding a unique id such as DOI for each reference via the crossref site. It can be used as an important metadata that describes the reference. Finding...

We continue our experiments with the corpus 2. In the previous post, we showed that a well-defined set of three different feature types improves note classification accuracy. Now we verify the usefulness of note...

This part of experiments constitutes the use of external proper noun lists. To overcome the miss-annotation between people name and place, we think of using a set of proper noun lists. People name and...

For the moment, we leave the note classification problem alone and return to the CRF learning on the corpus 1. After the detailed evaluation and revision of the automatic reference annotation result, we now...

In this posting, we present our last four strategies that add one by one the different binary local feature types. Strategy 7 : input + non-weighted global features + a binary local feature (posspage)...

Strategy 5 : input + 12 feature types + weighted global features Features M. et M. , « Aspects du droit dans marocain » , Droit et Société , , p. .ALLCAP INITIAL STARTINITIAL...

For the experiments, we used a well-known implementation of Support Vector Machines, SVMlight developed by Thorsten Joachims of Cornell University. The learning and test data for this program should be represented as the following format:...