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ISBN: 978-972-8939-25-0 © 2010 IADIS3.3.2 Experiment 2 (Adaptation Filter)In the experiment 2, we evaluated how we can keep the precision using the adaptation filter for the 16Japanese car manufacturers. Because the adaptation filter uses the hierarchical structure of ontology asmentioned above, we assumed here that Japan car is a subclass of Car and US car is also a subclass of Car inthe same level as Japan car like Fig.5. As the first seeds we registered {"Nissan", "Honda"} and {"GM","Ford", "Chrysler"} to Japan and US car respectively. Then, we repeated the procedure of the experiment 1with the adaptation filter to eliminate the instances which seems to belong to a different class (US car).Evaluation metrics are as follows.Recall = (3 + ∆ ) / 16Precision = (3 +∆ ) / (3 + ∆ + irrelevant instances), where ∆ is the registered correct instancesThe result is shown in Fig.7 (note that 0 time of the precision is omitted here). In terms of the precision,the NEE was 19.5 % at the 7th time due to US and European manufacturers included in the instances. But,the NEE with the adaptation filter got 26.1 %, and the gap was extending over time. As a consequence, weconfirmed the adaptation filter has effect to raise the precision.However, in terms of the recall, the adaptation filter remained 66.7 % at the 7th time, although NamedEntity Extraction achieved 100 % at that time. It's because some Japan car instances were also eliminatedtogether with the irrelevant terms.R ecalle c all100%90%80%70%60%50%40%30%20%NEE NEE w / Filter10%0%0 1 2 3 4 5 6 7Tim ePrec P c isionn30%25%20%15%10%5%0%1 2 3 4 5 6 7Tim eNEENEE w / FilterFigure 7. Result of experiment 24. PROPERTY RECOMMENDATION4.1 Property Recommendation with Named Entity ExtractionAs well as for the instances, it would be difficult to register every property without any help. Propertyrecommendation collects the properties using the NEE for the bootstrapping as well. But, in case of theproperty, we use three properties belonging to a class and an instance of the class as the query to collect theweb pages. This is because adding the instances would be useful to collect the related web pages like productspecification pages. The seeds for the NEE also include three properties and an instance. For example, if theuser puts "optical zoom", "digital zoom" and "pixels" to a camera class, then the property recommendationtakes those three properties and an instances of the camera, and extracts other properties like "focal length","sensitivity", and "shutter speed" to recommend for the user. After that, the seeds are changed to two oldproperties, one new property, and one new instance. In essence, the NEE using the bootstrapping is to extractterms written in the same style. So, we can expect that the seeds in different levels, that is, the property andthe instance do not work well. But, most of the product specification pages have a product name at thebeginning, then its specs (properties) later, so that we considered this seed combination would not affect somuch for the property extraction.108