TIDM: Topic-Specific Information Detection Model
نویسندگان
چکیده
منابع مشابه
Traffic Incident Detection Using Probabilistic Topic Model
Tra c congestion is quite common in urban settings, and is not always caused by tra c incidents. In this paper, we propose a simple method for detecting tra c incidents by using probe-car data to compare usual and current tra c states, thereby distinguishing incidents from spontaneous congestion. First, we introduce a tra c state model based on a probabilistic topic model to describe tra c stat...
متن کاملGraph-based Model for Topic Detection
In this paper, a novel graph-based model (GBM) is proposed for topic detecting. Different from existing statistical methods, our proposed model considers more semantic factors which combines named entity and dependency relation between words derived from a dependency parse tree. In our model, a graph is constructed for representing words and their association. By utilizing spectral clustering a...
متن کاملA Sequential Latent Topic-Based Readability Model for Domain-Specific Information Retrieval
In domain-specific information retrieval (IR), an emerging problem is how to provide different users with documents that are both relevant and readable, especially for the lay users. In this paper, we propose a novel document readability model to enhance the domain-specific IR. Our model incorporates the coverage and sequential dependency of latent topics in a document. Accordingly, two topical...
متن کاملTopic-Specific Link Analysis using Independent Components for Information Retrieval
There has been mixed success in applying semantic component analysis (LSA, PLSA, discrete PCA, etc.) to information retrieval. Previous experiments have shown that high-fidelity language models do not imply good quality retrieval. Here we combine link analysis with discrete PCA (a semantic component method) to develop an auxiliary score for information retrieval that is used in post-filtering d...
متن کاملUtilizing Temporal Information in Topic Detection and Tracking
The harnessing of time-related information from text for the use of information retrieval requires a leap from the surface forms of the expressions to a formalized time-axis. Often the expressions are used to form chronological sequences of events. However, we want to be able to determine the temporal similarity, i.e., the overlap of temporal references of two documents and use this similarity ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2017
ISSN: 1877-0509
DOI: 10.1016/j.procs.2017.11.365