Hey Wei,
> Considering the limited time, I put the support for google mention corpus
> as an optional work in the proposal. Is that ok?
I don't know if this is okay, I will have to discuss this with the other
mentors.
Best,
Jo
On Fri, May 3, 2013 at 2:17 PM, Wang Wei <[email protected]> wrote:
> Hi Jo,
>
> Thanks for your suggestions. I checked Mahout's website. It does support
> LDA. So I think we can train the entity-topic model on hadoop by following
> Mahout's LDA implementation.
> Considering the limited time, I put the support for google mention corpus
> as an optional work in the proposal. Is that ok?
>
> Best Regards,
> Wei
>
>
> On Fri, May 3, 2013 at 12:24 AM, Wang Wei <[email protected]> wrote:
>
>> Hi all,
>>
>> Thanks a lot for your comments. I have just updated my proposal. Looking
>> forward to your further feedback.
>>
>> Best Regards,
>> Wei
>>
>>
>> On Wed, May 1, 2013 at 5:59 PM, Joachim Daiber
>> <[email protected]>wrote:
>>
>>> I was referring to the layout of the formulas. Here is a screenshot.
>>>
>>> Jo
>>>
>>>
>>> On Wed, May 1, 2013 at 11:14 AM, Wang Wei <[email protected]> wrote:
>>>
>>>> Hi Jo,
>>>>
>>>> Thanks for your comments.
>>>>
>>>>
>>>>
>>>> - there is a formating problem for me starting with your github
>>>> account
>>>>
>>>> what do you mean by formating problem?
>>>>
>>>>
>>>> - could you fix the formulas? do you mean the formulas in my
>>>> proposal?
>>>>
>>>>
>>>>
>>>> I revised the paragraph for introducing the three models. (Still not
>>>> good enough..., I'll try to improve it later)
>>>>
>>>>
>>>>
>>>>
>>>> On Wed, May 1, 2013 at 2:37 PM, Wang Wei <[email protected]> wrote:
>>>>
>>>>> Hi Jo,
>>>>>
>>>>> I revised my proposal by adding the topic-based disambiguation method.
>>>>> Actually, I found a mistake in my previous discussion on the topic-based
>>>>> model. The topic-based model jointly models *the context
>>>>> compatibility(which I missed)* and topic coherence. Thus, it can
>>>>> perform well for both topic related and non-related entities. It is also a
>>>>> generative model.
>>>>>
>>>>> Thanks.
>>>>>
>>>>> Regards,
>>>>> Wei
>>>>>
>>>>>
>>>>> On Mon, Apr 29, 2013 at 10:03 PM, Wang Wei <[email protected]>wrote:
>>>>>
>>>>>> Hi Jo,
>>>>>>
>>>>>> I will think about the disambiguation part and revise my proposal.
>>>>>> Thanks.
>>>>>>
>>>>>> Best Regards,
>>>>>> Wei Wang
>>>>>>
>>>>>>
>>>>>> On Mon, Apr 29, 2013 at 7:57 PM, Wang Wei <[email protected]>wrote:
>>>>>>
>>>>>>> Hi Jo,
>>>>>>>
>>>>>>> I read the proposal of the topic extraction work from last year's
>>>>>>> GSoC. Yes, the topic-based disambiguation method is based on the LDA
>>>>>>> model.
>>>>>>> But their objectives are different: topic extraction is to assign topic
>>>>>>> categories for a document, while topic-based disambiguation is to
>>>>>>> disambiguate entities based on the document's topic. For example, if a
>>>>>>> document's topic is about 'mobile phones', then word 'Apple' would
>>>>>>> likely
>>>>>>> be assigned as Apple Inc. . But, as I mentioned in my proposal, for
>>>>>>> topic
>>>>>>> related entities, they can be disambiguated correctly; for other
>>>>>>> entities, they are not guaranteed to be disambiguated correctly by
>>>>>>> topic-based disambiguation method.
>>>>>>>
>>>>>>> In addition, for the generative model(the default disambiguation
>>>>>>> model), it has a strong assumption: p(c|e)=p_e(t_1) p_e(t_2)...p_e(t_n),
>>>>>>> i.e., the terms are independent given the entity e. Some improvements
>>>>>>> may
>>>>>>> be achieved if this assumption is removed.
>>>>>>>
>>>>>>> Thanks.
>>>>>>>
>>>>>>> Best Regards,
>>>>>>> Wei Wang
>>>>>>>
>>>>>>>
>>>>>>> On Mon, Apr 22, 2013 at 2:30 AM, Joachim Daiber <
>>>>>>> [email protected]> wrote:
>>>>>>>
>>>>>>>> Hey,
>>>>>>>>
>>>>>>>> you can have a look at Hector's github repository from last GSoC
>>>>>>>> (this is not merged into the main branch yet):
>>>>>>>>
>>>>>>>> https://github.com/hunterhector/dbpedia-spotlight
>>>>>>>>
>>>>>>>> I think this was the paper he implemented:
>>>>>>>>
>>>>>>>> Han, X., 2011. Collective Entity Linking in Web Text : A Graph-Based
>>>>>>>> Method. In *Proceedings of the 34th international ACM SIGIR
>>>>>>>> conference on Research and development in Information*. pp.
>>>>>>>> 765-774.
>>>>>>>>
>>>>>>>> Best,
>>>>>>>> Jo
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Sun, Apr 21, 2013 at 6:22 PM, Wang Wei <[email protected]>wrote:
>>>>>>>>
>>>>>>>>> Hi Jo,
>>>>>>>>>
>>>>>>>>> I am trying to learning something about the idea for "efficient
>>>>>>>>> graph based disambiguation". However, the introduction is very short.
>>>>>>>>> Do
>>>>>>>>> you have any further materials for the disambiguation methods used by
>>>>>>>>> db-pedia? In the disambiguation code directory[1], which one is graph
>>>>>>>>> based?
>>>>>>>>>
>>>>>>>>> Thanks a lot.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Best Regards,
>>>>>>>>> Wei Wang
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
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