Using Wikipedia knowledge to improve text classification

What’s New? Analysing Language-Specific Wikipedia Entity Contexts to Support Entity-Centric News Retrieval

“…Examples include information retrieval [4,14,18], named entity disambiguation [1,2,7,8,11,12], text classification [25] and entity ranking [10]. To extract the content of an entity context, many researches directly used the Wikipedia article describing the entity [1,2,8,9,14,[25][26][27]; some works extended the article with all the other Wikipedia articles linked to the Wikipedia article describing the entity [6,7,12]; while some only considered the first paragraph of the Wikipedia article describing the entity [2]. Different from these approaches, our Graph-based approach not only employs in-links and languagelinks to broaden the article set that is likely to mention the entity, but also performs a finer-grained process: extracting the sentences that mention the entity, such that all the sentences in our context are closely related to the target entity.…”

“…As to the context-based representation vector of the entity, [1,11] defined it as the tf-idf/word count/binary occurrence values of all the vocabulary words in the context content; [2,19] defined it as the word count/binary occurrence values of other entities in the context content; [5,6,9,14,25] defined it as the tf-idf similarity values between the target entity's context content and other entities' context contents from Wikipedia; [27] defined it as the visiting probability from the target entity to other entities from Wikipedia; [7,26] used a measurement based on the common entities linked to the target entity and other entities from Wikipedia. Different from all former researches, we employ aspect weights that have a different interpretation of the frequency and selectivity than the typical tf-idf values and take co-occurrence and language specificity of the aspects into account.…”

“…Some researches [1,2,9,12,14,25] also employed category-links to the Wikipedia article describing the entity. Since the category structure of Wikipedia is language-specific, it is hard to gain insights about cross-lingual context similarity for our case.…”

Similarity assessment for removal of noisy end user license agreements

“…In fact, it has been found in several experiments that more sophisticated representations do not yield any significant increase in effectiveness [34], although there are some recent approaches that have shown promise. For example, Wang automatically constructed a thesaurus of concepts from Wikipedia and introduced a unified framework to expand the bag-of-words representation with semantic relations [39]. More research is needed in order to establish whether this type of expansion really increases performance significantly over the traditional model.…”

Tagging Scientific Publications Using Wikipedia and Natural Language Processing Tools

“…Wikipedia was already applied in many studies on conceptualizing and contextualizing document collections. To name just a few recent examples, applications include clustering [3,4], assigning readable labels to the obtained document clusters [5,6], facilitating classification [7], or extracting keywords [8]. However, not much is known about the effectiveness of Wikipedia when it comes to processing scientific texts.…”