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Table 3: Generated average rating compared to actual
average rating (scale of 1 to 10).
Domain MSE
Mp3 Player 0.4722
Vacuum Cleaner 1.0230
Digital Camera 0.4327
Printer 0.5029
Television 1.0427
Baby Products 0.1623
Washing Machine 0.6845
Fridge-Freezer 0.8149
Software 0.5195
Cooker 1.0354
Laptop 0.9737
Mobile Phones 0.8148
Toys 0.9229
5 CONCLUSIONS
In this paper, we propose building a product review
summarizer which will process all the reviews of a
product and summarize them in a manner that is
easy for reading and comparison. The summarizer
first extracts a list of aspects along with their
corresponding sentiment words. After classifying the
polarity of these sentiment words, we can determine
the polarity associated with these aspects. It then
combines different aspects together to form a
summary consisting of a compressed list of aspects
and their ratings. The experimental results
demonstrate that the summarizer is accurate and
promising. Our future work will focus on enhancing
the aspect/sentiment extractor to learn extraction
rules automatically. We are also looking into better
visualization and product comparison mechanisms.
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