The LIFE Model v1.1

Extract: This document draws together feedback, discussion and review of the LIFE Model from a number of sources: 1. The LIFE and LIFE2 Project Teams, and the staff of their institutions 2. Feedback from review by independent economics expert 3. The LIFE Project Conference 4. Early adopters of the Life Model (particularly the Royal Danish Library, State Archives and the State and University Library, Denmark) The result is a revision of the LIFE Model which was first published in 2006 by the LIFE Project . In line with the objectives of the LIFE2 Project, this revision aims to: 1. fix outstanding anomalies or omissions in the Model 2. scope and define the Model and its components more precisely 3. facilitate useful and repeatable mapping and costing of digital lifecycles

Generating indicative-informative summaries with SumUM

We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

Structural variation in generated health reports

We present a natural language generator that produces a range of medical reports on the clinical histories of cancer patients, and discuss the problem of conceptual restatement in generating various textual views of the same conceptual content. We focus on two features of our system: the demand for 'loose paraphrases' between the various reports on a given patient, with a high degree of semantic overlap but some necessary amount of distinctive content; and the requirement for paraphrasing at primarily the discourse level

Closing the loop: assisting archival appraisal and information retrieval in one sweep

In this article, we examine the similarities between the concept of appraisal, a process that takes place within the archives, and the concept of relevance judgement, a process fundamental to the evaluation of information retrieval systems. More specifically, we revisit selection criteria proposed as result of archival research, and work within the digital curation communities, and, compare them to relevance criteria as discussed within information retrieval's literature based discovery. We illustrate how closely these criteria relate to each other and discuss how understanding the relationships between the these disciplines could form a basis for proposing automated selection for archival processes and initiating multi-objective learning with respect to information retrieval