By Witold Abramowicz
This ebook comprises the refereed lawsuits of the eleventh overseas convention on company info platforms, BIS 2008, held in Innsbruck, Austria, in might 2008. The forty-one revised complete papers have been rigorously reviewed and chosen inclusion within the e-book. The contributions hide learn developments in addition to present achievements and leading edge advancements within the zone of recent company info structures. they're grouped in sections on company procedure administration, provider discovery and composition, ontologies, info retrieval, company source making plans, interoperability, mobility and contexts, wikis and folksonomies, and principles and semantic queries.
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Additional info for Business Information Systems: 11th International Conference, BIS 2008, Innsbruck, Austria, May 5-7, 2008, Proceedings (Lecture Notes in Business Information Processing)
There are various ways to do cross-validating, and in this paper, the weight of each entity pair is computed according to the number of its occurrence. For example, if there are two different addresses A1 and A2 associated to the same name N1, we count the number of the occurrence of pair (N1, A1) and pair (N1, A2). If the number of occurrences of pair (N1, A1) is larger than the other, we think the first one is more believable and make it as the correct answer. The experiment results are listed in Table 6: Table 6.
And the Gazetteer contains a fivelevel hierarchical tree. g. 3 Evaluation Measures for Recognition We employ Precision, Recall and F-measure to evaluate our entity recognition results. In the evaluation, if the extracted entities (name or address) can exactly match to the annotated ones, we regard it as a correct extraction. 4 Experiments on Chinese Organization Name Recognition In this experiment, we compared our system with the baseline system over the 500 HTML pages. For each web page of our test data, we first parse it into a DOM-Tree Chinese Organization Entity Recognition and Association on Web Pages 21 and conduct our recognition and association procedures on it.
If the two entities are associated, store them in the local node and pass all the unassociated entities to their parent. Go to step 2. Step 2: In internal nodes, receive all the unassociated entities from its children from left to right and insert them into a text string orderly. Associate these entities like that in step 1 and pass all the unassociated entities to their parents. Go to step 3. Step 3: If it is not the root node, go to step 2. Stop otherwise. We only present this simple association algorithm in this paper and we will study it in our future work.
Business Information Systems: 11th International Conference, BIS 2008, Innsbruck, Austria, May 5-7, 2008, Proceedings (Lecture Notes in Business Information Processing) by Witold Abramowicz