Collaboratively Tracking Interests for User Clustering in Streams of Short Texts
- Diploma
- BCA
- B.Sc
- B.Tech/B.E.
- M.Sc
- MCA
- M.Tech/M.E.
Abstract—In this paper, we aim at tackling the problem of user clustering in the context of their published short text streams. Clustering users by short text streams is more challenging than in the case of long documents associated with them as it is dif?cult to track users’ dynamic interests in streaming sparse data. To obtain better user clustering performance, we propose two user collaborative interest tracking models that aim at tracking changes of each user’s dynamic topic distributions in collaboration with their followees’ dynamic topic distributions, based both on the content of current short texts and the previously estimated distributions. Our models can be either short-term or long-term dependency topic models. Short-term dependency model collaboratively tracks users’ interests based on users’ topic distributions at the previous time period only, whereas long-term dependency model collaboratively tracks users’ interests based on users’ topic distributions at multiple time periods in the past. We also propose two collapsed Gibbs sampling algorithms for collaboratively inferring users’ dynamic interests for their clustering in our short-term and long-term dependency topic models, respectively. We evaluate our proposed models via a benchmark dataset consisting of Twitter users and their tweets. Experimental results validate the effectiveness of our proposed models that integrate both users’ and their collaborative interests for user clustering by short text streams
4 years ago
DOWNLOAD
Related Topics
Abstract—Ride-sharing (RS) has great values in saving energy and alleviating traf?c pressure. Existing studies can be improved for better ef?ciency. Therefore, we propose a new ride-sharing model, where each driver has a requirement that if the driver shares a ride with a rider, the shared route ...
- Diploma
- BCA
- B.Sc
- B.Tech/B.E.
- M.Sc
- MCA
- M.Tech/M.E.
Technologies
Abstract—With the wide application of location-based socialnetworks (LBSNs), point-of-interest (POI)recommendation has become one of the major services in LBSNs. The behaviors of users in LBSNs are mainly checking in POIs, and these checking-in behaviors are influenced by user’s behavior habits a...
- Diploma
- BCA
- B.Sc
- B.Tech/B.E.
- M.Sc
- MCA
- M.Tech/M.E.
Technologies
Abstract—Finding relevant papers is a non-trivial problem for scholars due to the tremendous amount of academic information in the era of scholarly big data. Scienti?c paper recommendation systems have been developed to solve such problem by recommending relevant papers to scholars. However, prev...
- Diploma
- BCA
- B.Sc
- B.Tech/B.E.
- M.Sc
- MCA
- M.Tech/M.E.
Technologies
Abstract—Grounded on communication theories, we propose to use a data-mining algorithm to detect communication patterns within a company to determine if such patterns may reveal the performance of the company. Speci?cally, we would like to ?nd out whether or not there exist any association relati...
- Diploma
- BCA
- B.Sc
- B.Tech/B.E.
- M.Sc
- MCA
- M.Tech/M.E.
Technologies
Abstract—We formulate a document summarization method to extract passage-level answers for non-factoid queries, referred as answer-biased summaries. We propose to use external information from related Community Question Answering (CQA) content to better identify answer bearing sentences. Three op...
- Diploma
- BCA
- B.Sc
- B.Tech/B.E.
- M.Sc
- MCA
- M.Tech/M.E.
Technologies
