3. The method of claim 1 , wherein comparing the descriptive context of the input item to the respective descriptive contexts of each of the plurality of other items to determine the respective levels of similarity between the input item and each of the plurality of other items comprises: generating, based at least in part on the descriptive context of the input item, a vector representing a semantic makeup of the descriptive context of the input item; and determining respective cosine similarities between the vector representing the semantic makeup of the descriptive context of the input item and each of a plurality of respective vectors representing respective semantic makeups of the respective descriptive contexts of the plurality of other items.
3. The method of claim 1 , wherein comparing the descriptive context of the input item to the respective descriptive contexts of each of the plurality of other items to determine the respective levels of similarity between the input item and each of the plurality of other items comprises: generating, based at least in part on the descriptive context of the input item, a vector representing a semantic makeup of the descriptive context of the input item; and determining respective cosine similarities between the vector representing the semantic makeup of the descriptive context of the input item and each of a plurality of respective vectors representing respective semantic makeups of the respective descriptive contexts of the plurality of other items. 4. The method of claim 3 , wherein the vector representing the semantic makeup of the descriptive context of the input item comprises at least one of: a Term Frequency-Inverse Document Frequency (TF-IDF) vector, a Latent Dirichlet Allocation TF-IDF (LDA-TFIDF) vector, or a Latent Semantic Indexing TF-IDF (LSI-TFIDF) vector.