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From Robin Anil <robin.a...@gmail.com>
Subject Re: Mahout In Action
Date Fri, 23 Apr 2010 17:25:40 GMT
Its not aimed at 0.3 per say. Right now its evolving with the code. For. eg.
the quality factor is something that will go in there. I keep updating the
code with the latest changes and so does Sean. There isnt much that got
affected by your latest commit though(it compiles). Though I haven't fully
tested the code with the dataset after the commit, something I plan to do
soon.

Robin

On Fri, Apr 23, 2010 at 9:51 PM, Jeff Eastman <jdog@windwardsolutions.com>wrote:

> I also wonder how much my recent clustering changes have affected the
> examples in the clustering sections. I know the book is currently aimed at
> Mahout 0.3 but users trying the examples with trunk may be frustrated by the
> recent changes in file naming. Do the examples exist in an unannotated
> version somewhere that I could get working again on trunk?
>
> On 4/23/10 9:10 AM, Sean Owen wrote:
>
>> Good eye, this was fixed in the manuscript a while ago.
>>
>> I will ping Manning to re-publish Chapters 1-6 since a lot of small
>> updates have happened since then.
>>
>> On Fri, Apr 23, 2010 at 4:53 PM, Jeff Eastman
>> <jdog@windwardsolutions.com>  wrote:
>>
>>
>>> Section 4.5.1 says:
>>> "The third line shows how it is based on item-item similarities, not
>>> user-user similarities as before. The algorithms are similar, but not
>>> entirely symmetric. They do have notably different properties. For
>>> instance,
>>> the running time of an item-based recommender scales up as the number of
>>> items increases, whereas a user-based recommender’s running time goes up
>>> as
>>> the number of users increases.
>>>
>>> This suggests one reason that you might choose an item-based recommender:
>>> if
>>> the number of users is relatively low compared to the number of items,
>>> the
>>> performance advantage could be significant."
>>>
>>> Shouldn't the second paragraph be?
>>>
>>> "This suggests one reason that you might choose an item-based
>>> recommender:
>>> if the number of users is relatively *high* compared to the number of
>>> items,
>>> the performance advantage could be significant."
>>>
>>>
>>>
>>>
>>
>>
>
>

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