We propose a supervised method of extracting event causalities like conduct slash-and-burn agriculture→exacerbate desertification from the web using semantic relation (between nouns), context, and association features. Experiments show that our method outperforms baselines that are based on state-of-the-art methods. We also propose methods of generating future scenarios like conduct slash-and-burn agriculture→exacerbate desertification→increase Asian dust (from China)→asthma gets worse.Experiments show that we can generate 50,000 scenarios with 68% precision. We also generated a scenario deforestation continues→global warming worsens→sea temperatures rise→vibrio parahaemolyticus fouls (water), which is written in no document in our input web corpus crawled in 2007. But the vibrio risk due to global warming was observed in Baker-Austin et al. (2013). Thus, we "predicted" the future event sequence in a sense.
We describe a browser for the past web. It can retrieve data from multiple past web resources and features a passive browsing style based on change detection and presentation. The browser shows past pages one by one along a time line. The parts that were changed between consecutive page versions are animated to reflect their deletion or insertion, thereby drawing the user's attention to them. The browser enables automatic skipping of changeless periods and filtered browsing based on user specified query.
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