Question

我正在寻找一种方法,以建立言行的等级。

背景: 我是“业余”的天然语言处理,现在,我感兴趣的问题之一是确定语义的等级。

例如,如果我有一套包含“超级”他人代表的单位,即:

[cat, dog, monkey, animal, bird, ... ]

我有兴趣利用任何技术,使我能够提取动物一词,而动物一词在本组内具有最有意义和最准确的表述。

Note: they are NOT the same in meaning. cat != dog != monkey != animal BUT cat is a subset of animal and dog is a subset of animal.

I know by now a lot of you will be telling me to use wordnet. Well, I will try to but I am actually interested in doing a very domain specific area which WordNet doesn t apply because: 1) Most words are not found in Wordnet 2) All the words are in another language; translation is possible but is to limited effect.

另一个例子是:

[ noise reduction, focal length, flash, functionality, .. ]

这样的功能包括本套内容。

我也尝试了拖网轮式轮.,在拖网等地应用了一些技术,但轮式轮.实际上也做了很多工作。

谁能向我介绍一下我的研究方向? (我可以使用任何东西)

Answer 1

它希望像你那样使用“hypernym/hyponym relations in WordNet,但由于语言和领域的特殊报道问题,实际上没有使用WordNet? 也就是说,如果你有特定领域的超婚关系,那么你就可以找到“超级”代表处,只寻找最接近的父母,把名单上的所有字都包括在内,或把其他所有字都归入名单上的最接近的节点。

首先,我要指出,世界主要语言的many的WordNets实际可查:rel=“nofollow noreferer”>。

为了获得,你可以使用斯诺等人提出的技术。 s rel=“nofollow noreferer”> 学习自动高分辨率探测的合成形态。也就是说,你可以从小块种子高分子开始,然后用它们培训一个班子在册中检测出高分泌。之后,你将利用来自贵领域的数据进行这一分类,以便编制一份具体领域的高分数字。

Answer 2

opinion mining and opinion analysis 民间s在决定什么词代表产品特点方面可以做相关工作,而不知道产品是什么。

A quick sketch of an idea for how you might do this, which I ve totally made up on the spot: Parse a bunch of sentences in the relevant domain; find the noun phrases and adjectives. Figure out which noun phrases are associated with which adjectives. Cluster the noun phrases together based on the set of adjectives used to describe them. Animals will tend together because they re going to be described by adjectives like "furry" or "cute", etc. (In particular, hierarchical clustering would probably be most appropriate.)

如果你尝试这样做,并且工作,请让我知道:

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