Vector Space Model (VSM) has been at the core of information retrieval for the past decades. VSM considers the documents as vectors in high dimensional space. In such a vector spa...
Requirements views, such as coverage and status views, are an important asset for monitoring and managing software development. We have developed a method that automates the proce...
Managing traceability data is an important aspect of the software development process. In this paper we investigate to what extent latent semantic indexing (LSI), an information r...
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
Concept location techniques are designed to help isolate sections of source code that relate to specific concepts. Blind Signal Separation techniques like Singular Value Decompos...
Latent Semantic Indexing (LSI) is an effective method to discover the underlying semantic structure of data. It has numerous applications in information retrieval and data mining....
Software engineers think about an existing software system in terms of high-level models. The high-level models are translated to source code and the concepts represented in these...
We present a class of models that are discriminatively trained to directly map from the word content in a query-document or documentdocument pair to a ranking score. Like Latent Se...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
As development on a software project progresses, developers shift their focus between different topics and tasks many times. Managers and newcomer developers often seek ways of un...
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...