Examining the Content Load of Part of Speech Blocks for Information Retrieval

We investigate the connection between part of speech (POS) distribution and content in language. We define POS blocks to be groups of parts of speech. We hypothesise that there exists a directly proportional relation between the frequency of POS blocks and their content salience. We also hypothesise that the class membership of the parts of speech within such blocks reflects the content load of the blocks, on the basis that open class parts of speech are more content-bearing than closed class parts of speech. We test these hypotheses in the context of Information Retrieval, by syntactically representing queries, and removing from them content-poor blocks, in line with the aforementioned hypotheses. For our first hypothesis, we induce POS distribution information from a corpus, and approximate the probability of occurrence of POS blocks as per two statistical estimators separately. For our second hypothesis, we use simple heuristics to estimate the content load within POS blocks. We use the Text REtrieval Conference (TREC) queries of 1999 and 2000 to retrieve documents from the WT2G and WT10G test collections, with five different retrieval strategies. Experimental outcomes confirm that our hypotheses hold in the context of Information Retrieval.