【摘要】：【目的】通過對電子商務(wù)評論文本的分析和處理,獲取有效的商家信譽(yù)信息,從客觀角度建立商家信譽(yù)維度體系。【方法】基于HNC理論的同行優(yōu)先原理和文本挖掘方法提出改進(jìn)的評論文本主題詞抽取方法和主題詞聚類算法,并進(jìn)行類簇標(biāo)簽抽取及各類簇權(quán)重計(jì)算�！窘Y(jié)果】生成商家信譽(yù)維度體系及各維度權(quán)重,以京東平臺手機(jī)評論文本為實(shí)例,構(gòu)建商家信譽(yù)維度體系,并對其進(jìn)行評價(jià),證明方法的可行性與有效性�！揪窒蕖渴蹾NC詞庫不全的影響需手工生成一部分字詞符號,在應(yīng)用到更大規(guī)模的評論文本處理時(shí)可能會存在限制�！窘Y(jié)論】利用本文提出的方法建立的商家信譽(yù)維度體系能夠客觀地反映出用戶真正關(guān)心的商品指標(biāo)。
[Abstract]:[objective] to obtain effective merchant credit information through the analysis and processing of electronic commerce comment texts, From the objective point of view, the dimension system of merchant reputation is established. [methods] based on the peer-first principle of HNC theory and the text mining method, an improved method of subject word extraction and clustering algorithm of comment text is proposed. And the cluster label extraction and all kinds of cluster weights are calculated. [results] the dimension system of merchant reputation and the weight of each dimension are generated. Taking the mobile phone comment text of JingDong platform as an example, the business reputation dimension system is constructed and evaluated. To prove the feasibility and effectiveness of the method. [limitations] affected by incomplete HNC lexicon, a part of the word symbols need to be generated manually. There may be some limitations in the application of this method to the larger comment text processing. [conclusion] the merchant reputation dimension system based on the method proposed in this paper can objectively reflect the commodity index that the user really cares about.
【作者單位】： 大連理工大學(xué)管理與經(jīng)濟(jì)學(xué)部;
【基金】：國家自然科學(xué)基金重點(diǎn)項(xiàng)目“社會化商務(wù)中參與者的信譽(yù)與信任機(jī)理及交易決策研究”(項(xiàng)目編號:71431002)的研究成果之一
【分類號】：TP391.1
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本文編號：2344040