STORIES in Time: A Graph-Based Interface for News Tracking and Discovery

Berendt, Bettina; Subasic, Ilija

doi:10.1109/wi-iat.2009.342

Cited by 15 publications

(9 citation statements)

References 22 publications

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“…A step further is taken by STORIES (Berendt & Subasic, 2009), a system that clusters documents that contain the same keywords and links them together according to their publication time. However, this work do not leverage state-of-the-art semantic analysis, hence it is not able to extract entities, facts and their relationships from documents.…”

Section: Related Workmentioning

confidence: 99%

Supporting sense-making and decision-making through time evolution analysis of open sources

Balboni

Marchetti

Colajanni

et al. 2015

2015 7th International Conference on Cyber Conflict: Architectures in Cyberspace

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Modern societies produce a huge amount of open source information that is often published on the Web in a natural language form. The impossibility of reading all these documents is paving the way to semantic-based technologies that are able to extract from unstructured documents relevant information for analysts. Most solutions extract uncorrelated pieces of information from individual documents; few of them create links among related documents and, to the best of our knowledge, no technology focuses on the time evolution of relations among entities. We propose a novel approach for managing, querying and visualizing temporal knowledge extracted from unstructured documents that can open the way to novel forms of sense-making and decision-making processes. We leverage state-of-the-art natural language processing engines for the semantic analysis of textual data sources to build a temporal graph database that highlights relationships among entities belonging to different documents and time frames. Moreover, we introduce the concept of temporal graph query that analysts can use to identify all the relationships of an entity and to visualize their evolution over time. This process enables the application of statistical algorithms that can be oriented to the automatic analysis of anomalies, state change detection, forecasting. Preliminary results demonstrate that the representation of the evolution of entities and relationships allows an analyst to highlight relevant events among the large amount of open source documents

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Section: Related Workmentioning

confidence: 99%

Supporting sense-making and decision-making through time evolution analysis of open sources

Balboni

Marchetti

Colajanni

et al. 2015

2015 7th International Conference on Cyber Conflict: Architectures in Cyberspace

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“…A contribution both to story tracking and to story visualization was made by Berendt and Subašić [13]. Their approach, called STORIES, extracts stories from articles on the Web by comparing the articles on the basis of story related term co-occurrence.…”

Section: Topic Detectionmentioning

confidence: 99%

Multiple developing news stories identified and tracked by social insects and visualized using the new galactic streams and concurrent streams metaphors

Sabo

Kovarova

Návrat

2015

HIS

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We have developed an approach to identification and tracking of currently unfolding news stories extracted from the news articles published on the Web. Our approach employs a set of agents to retrieve those articles from the Web that might refer to some developing news story. The set of agents is inspired by social insects, in particular by a bee colony. Bees identify popular terms, referred to as story words, relevant to the ongoing news stories and use them in foraging articles. This allows for a dynamic approach that reflects the changes in article space as new stories unfold and new articles are added. Subsequently a graph representation of the article space is constructed that contains retrieved articles and identified story words interconnected by edges according to relationships of relevance identified between elements of the graph. Stories are then extracted from the constructed graph by using Louvain method, commonly used to identify communities within modular graphs. Using this approach we have been able to identify news stories in a stream of articles retrieved from the Web with precision of 75.56%, with best precision generally achieved for recent news stories described by popular story words. Further we developed ways of visualization of multiple stories represented by sets of articles ordered in time. We propose two new metaphors both employing an exponential timeline. Both galactic streams and concurrent streams are highly suitable for visualizing multiple developing stories.

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“…A large number of research efforts have focused on enhancing and improving document representations by applying Natural Language Processing (NLP) technology such as Named Entity Recognition (NER) (Yang et al, 1999, Makkonen et al, 2004, Kumaran & Allan, 2004, Zhang et al, 2004. Some research tended towards interactive TDT through casting its attention on the graphical user interface (GUI), rather than on laboratory experiments such as TDT Lighthouse (Leuski & Allan, 2000), TimeMine (Swan & Allan, 2000), Topic Tracking Visualization Tool (Jones & Gabb, 2002), Event Organizer (Allan et al, 2005), Stories in Time (Berendt & Subasic, 2009) and Interactive Event Tracking System (iEvent) interface (Mohd et al, 2012), which are all examples of TDT studies that investigate some approaches to enhancing and improving TDT systems' and users' performance. Based on the works reviewed, none of them investigate the effectiveness of their interfaces using the combination of a bag of words (BOW) and named entities (NE) approach.…”

Section: Related Workmentioning

confidence: 99%

Investigating the Combination of Bag of Words and Named Entities Approach in Tracking and Detection Tasks among Journalists

Mohd¹,

Bashaddadh²

2014

Journal of Information Science Theory and Practice

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STORIES in Time: A Graph-Based Interface for News Tracking and Discovery

Cited by 15 publications

References 22 publications

Supporting sense-making and decision-making through time evolution analysis of open sources

Supporting sense-making and decision-making through time evolution analysis of open sources

Multiple developing news stories identified and tracked by social insects and visualized using the new galactic streams and concurrent streams metaphors

Investigating the Combination of Bag of Words and Named Entities Approach in Tracking and Detection Tasks among Journalists

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