Система реферирования мультимодальной информации

Розглянуто процес реферування мультимодальної інформації. Тобто початкова інформація може представлятися у вигляді тексту, зображення, аудіо або відео. Пропонується модель процесу реферування, поліпшена за рахунок введення додаткового етапу, що дозволяє обробляти мультимодальну інформацію. Наводяться алгоритм функціонування системи реферування на цьому етапі та модель процесу перетворення початкового документа у внутрішній формат системи.Рассмотрен процесс реферирования мультимодальной информации. То есть исходная информация может представляться в виде текста, изображения, аудио или видео. Предлагается модель процесса реферирования, улучшенная за счёт введения дополнительного этапа, позволяющего обрабатывать мультимодальную информацию. Приводятся алгоритм функционирования системы реферирования на этом этапе и модель процесса преобразования исходного документа во внутренний формат системы.This paper considers the process of multimodal information summarization. Input information can appear as a text, image, audio or video. There had been suggested the model of summarization process, improved by introducing of the additional stage, which allows to process multimodal information. The algorithm of the summarization system functioning on mentioned stage and model of transformation process of input document to the system's internal format had also been described

Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach

This article describes a knowledge-based method for generating multimedia descriptions that summarize the behavior of dynamic systems. We designed this method for users who monitor the behavior of a dynamic system with the help of sensor networks and make decisions according to prefixed management goals. Our method generates presentations using different modes such as text in natural language, 2D graphics and 3D animations. The method uses a qualitative representation of the dynamic system based on hierarchies of components and causal influences. The method includes an abstraction generator that uses the system representation to find and aggregate relevant data at an appropriate level of abstraction. In addition, the method includes a hierarchical planner to generate a presentation using a model with dis- course patterns. Our method provides an efficient and flexible solution to generate concise and adapted multimedia presentations that summarize thousands of time series. It is general to be adapted to differ- ent dynamic systems with acceptable knowledge acquisition effort by reusing and adapting intuitive rep- resentations. We validated our method and evaluated its practical utility by developing several models for an application that worked in continuous real time operation for more than 1 year, summarizing sen- sor data of a national hydrologic information system in Spain

Feasibility of using citations as document summaries

The purpose of this research is to establish whether it is feasible to use citations as document summaries. People are good at creating and selecting summaries and are generally the standard for evaluating computer generated summaries. Citations can be characterized as concept symbols or short summaries of the document they are citing. Similarity metrics have been used in retrieval and text summarization to determine how alike two documents are. Similarity metrics have never been compared to what human subjects think are similar between two documents. If similarity metrics reflect human judgment, then we can mechanize the selection of citations that act as short summaries of the document they are citing. The research approach was to gather rater data comparing document abstracts to citations about the same document and then to statistically compare those results to several document metrics; frequency count, similarity metric, citation location and type of citation. There were two groups of raters, subject experts and non-experts. Both groups of raters were asked to evaluate seven parameters between abstract and citations: purpose, subject matter, methods, conclusions, findings, implications, readability, andunderstandability. The rater was to identify how strongly the citation represented the content of the abstract, on a five point likert scale. Document metrics were collected for frequency count, cosine, and similarity metric between abstracts and associated citations. In addition, data was collected on the location of the citations and the type of citation. Location was identified and dummy coded for introduction, method, discussion, review of the literature and conclusion. Citations were categorized and dummy coded for whether they refuted, noted, supported, reviewed, or applied information about the cited document. The results show there is a relationship between some similarity metrics and human judgment of similarity.Ph.D., Information Studies -- Drexel University, 200