Query-free news search

Many daily activities present information in the form of a stream of text, and often people can benefit from additional information on the topic discussed. TV broadcast news can be treated as one such stream of text; in this paper we discuss finding news articles on the web that are relevant to news currently being broadcast.We evaluated a variety of algorithms for this problem, looking at the impact of inverse document frequency, stemming, compounds, history, and query length on the relevance and coverage of news articles returned in real time during a broadcast. We also evaluated several postprocessing techniques for improving the precision, including reranking using additional terms, reranking by document similarity, and filtering on document similarity. For the best algorithm, 84%-91% of the articles found were relevant, with at least 64% of the articles being on the exact topic of the broadcast. In addition, a relevant article was found for at least 70% of the topics

Write While You Search: Ambient Searching of a Digital Library in the Context of Writing

We consider ideas for a tighter integration of searching a digital library while writing a paper. A prototype system based on web services is described which allows us to explore the design space of ambient search tools to support and inspire the writing process.published or submitted for publicationis peer reviewe

An Evaluation of Link Neighborhood Lexical Signatures to Rediscover Missing Web Pages

For discovering the new URI of a missing web page, lexical signatures, which consist of a small number of words chosen to represent the "aboutness" of a page, have been previously proposed. However, prior methods relied on computing the lexical signature before the page was lost, or using cached or archived versions of the page to calculate a lexical signature. We demonstrate a system of constructing a lexical signature for a page from its link neighborhood, that is the "backlinks", or pages that link to the missing page. After testing various methods, we show that one can construct a lexical signature for a missing web page using only ten backlink pages. Further, we show that only the first level of backlinks are useful in this effort. The text that the backlinks use to point to the missing page is used as input for the creation of a four-word lexical signature. That lexical signature is shown to successfully find the target URI in over half of the test cases.Comment: 24 pages, 13 figures, 8 tables, technical repor

Human Document Classification Using Bags of Words

Humans are remarkably adept at classifying text documents into cate-gories. For instance, while reading a news story, we are rapidly able to assess whether it belongs to the domain of finance, politics or sports. Automating this task would have applications for content-based search or filtering of digital documents. To this end, it is interesting to investigate the nature of information humans use to classify documents. Here we report experimental results suggesting that this information might, in fact, be quite simple. Using a paradigm of progressive revealing, we determined classification performance as a function of number of words. We found that subjects are able to achieve similar classification accuracy with or without syntactic information across a range of passage sizes. These results have implications for models of human text-understanding and also allow us to estimate what level of performance we can expect, in principle, from a system without requiring a prior step of complex natural language processing