Generating and Retrieving Text Segments for Focused Access to Scientific Documents

When presented with a retrieved document, users of a search engine are usually left with the task of pinning down the relevant information inside the document. Often this is done by a time-consuming combination of skimming, scrolling and Ctrl+F. In the setting of a digital library for scientific literature the issue is especially urgent when dealing with reference works, such as surveys and handbooks, as these typically contain long documents. Our aim is to develop methods for providing a “go-read-here” type of retrieval functionality, which points the user to a segment where she can best start reading to find out about her topic of interest. We examine multiple query-independent ways of segmenting texts into coherent chunks that can be returned in response to a query. Most (experienced) authors use paragraph breaks to indicate topic shifts, thus providing us with one way of segmenting documents. We compare this structural method with semantic text segmentation methods, both with respect to topical focus and relevancy. Our experimental evidence is based on manually segmented scientific documents and a set of queries against this corpus. Structural segmentation based on contiguous blocks of relevant paragraphs is shown to be a viable solution for our intended application of providing “go-read-here” functionality.