Accounting for Language Changes over Time in Document Similarity Search
2015-07-07
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Accounting for Language Changes over Time in Document Similarity Search
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2015-07-07
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Abstract
Given a query document, ranking the documents in a collection based on how similar
they are to the query is an essential task with extensive applications. For collections
that contain documents whose creation dates span several decades, this task is further
complicated by the fact that the language changes over time. For example, many terms
add or lose one or more senses to meet people's evolving needs. To address this problem,
we present methods that take advantage of two types of information in order to account
for the language change. The first is the citation network that often exists within
the collection, which can be used to link related documents with significantly
different creation dates (and hence different language use). The second is the changes
in the usage frequency of terms that occur over time, which can indicate changes in
their senses and uses. These methods utilize the above information while estimating
the representation of both documents and terms within the context of non-probabilistic
static and dynamic topic models. Our experiments on two real-world datasets that
span more than 40 years show that our proposed methods improve the retrieval
performance of existing models and that these improvements are statistically significant.
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Morsy, Sara; Karypis, George. (2015). Accounting for Language Changes over Time in Document Similarity Search. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215976.
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