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April 2017
WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion
Publisher: International World Wide Web Conferences Steering Committee
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 8, Downloads (12 Months): 32, Downloads (Overall): 32
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Predicting the popularity of online content is highly valuable in many applications and has been studied for several years. However, existing models either work in population level---all messages are assumed to follow similar popularity dynamics, lacking flexibility to capture the intrinsic complexity of popularity dynamics, or work in individual level---the ...
Keywords:
information cascades, social media, popularity prediction
2
April 2017
WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion
Publisher: International World Wide Web Conferences Steering Committee
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 6, Downloads (12 Months): 12, Downloads (Overall): 12
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Automatic taxonomy construction aims to build a categorization system without human efforts. Traditional textual pattern based methods extract hyponymy relation in raw texts. However, these methods usually yield low precision and recall. In this paper, we propose a method to automatically find diffusing attributes to a category from Wikipedia infoboxes. ...
Keywords:
category, wikipedia, diffusing attribute, taxonomy
3
February 2017
Information Retrieval: Volume 20 Issue 1, February 2017
Publisher: Kluwer Academic Publishers
Query recommendation has long been considered a key feature of search engines, which can improve users' search experience by providing useful query suggestions for their search tasks. Most existing approaches on query recommendation aim to recommend relevant queries, i.e., alternative queries similar to a user's initial query. However, the ultimate ...
Keywords:
Query recommendation, Query utility, Search behavior, Dynamic Bayesian network
4
January 2017
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Issue: Mobile Social Multimedia Analytics in the Big Data Era and Regular Papers: Volume 8 Issue 3, April 2017
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 13, Downloads (12 Months): 84, Downloads (Overall): 84
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The queries issued to search engines are often ambiguous or multifaceted, which requires search engines to return diverse results that can fulfill as many different information needs as possible; this is called search result diversification . Recently, the relational learning to rank model, which designs a learnable ranking function following ...
Keywords:
Search result diversification, relational learning to rank, diversity evaluation measure
5
November 2016
Scientometrics: Volume 109 Issue 2, November 2016
Publisher: Springer-Verlag New York, Inc.
Scientific impact evaluation is a long-standing problem in scientometrics. Graph-ranking methods are often employed to account for the collective diffusion process of scientific credit among researchers or their publications. One key issue, however, is still up in the air: what is the appropriate level for scientific credit diffusion, researcher level ...
Keywords:
Credit diffusion, Scientific impact, Authorship citation network
6
November 2016
IEEE Transactions on Knowledge and Data Engineering: Volume 28 Issue 11, November 2016
Publisher: IEEE Educational Activities Department
There is always a lack of a cluster validity function and optimization strategy to find out clusters and catch the evolution trend of cluster structures on a categorical data stream. Therefore, this paper presents an optimization model for clustering categorical data streams. In the model, a cluster validity function is ...
7
October 2016
CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 6, Downloads (12 Months): 59, Downloads (Overall): 59
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Machine learning algorithms have become the key components in many big data applications. However, the full potential of machine learning is still far from been realized because using machine learning algorithms is hard, especially on distributed platforms such as Hadoop and Spark. The key barriers come from not only the ...
Keywords:
directed acyclic graph, dataflow, machine learning process
8
September 2016
RecSys Challenge '16: Proceedings of the Recommender Systems Challenge
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 26, Downloads (12 Months): 154, Downloads (Overall): 154
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In this paper, we present an ensemble method for job recommendation to ACM RecSys Challenge 2016. Given a user, the goal of a job recommendation system is to predict those job postings that are likely to be relevant to the user 1 . Firstly, we analyze the train dataset and ...
Keywords:
recsys challenge 2016, LSI, ensemble, top-n recommendation, word2vec
9
July 2016
IJCAI'16: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence
Publisher: AAAI Press
Recently, Word2Vec tool has attracted a lot of interest for its promising performances in a variety of natural language processing (NLP) tasks. However, a critical issue is that the dense word representations learned in Word2Vec are lacking of interpretability. It is natural to ask if one could improve their interpretability ...
10
July 2016
IJCAI'16: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence
Publisher: AAAI Press
Predicting anchor links across social networks has important implications to an array of applications, including cross-network information diffusion and cross-domain recommendation. One challenging problem is: whether and to what extent we can address the anchor link prediction problem, if only structural information of networks is available. Most existing methods, unsupervised ...
11
July 2016
IJCAI'16: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence
Publisher: AAAI Press
Semantic matching, which aims to determine the matching degree between two texts, is a fundamental problem for many NLP applications. Recently, deep learning approach has been applied to this problem and significant improvements have been achieved. In this paper, we propose to view the generation of the global interaction between ...
12
July 2016
SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 14, Downloads (12 Months): 224, Downloads (Overall): 224
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Search result diversification has attracted considerable attention as a means to tackle the ambiguous or multi-faceted information needs of users. One of the key problems in search result diversification is novelty, that is, how to measure the novelty of a candidate document with respect to other documents. In the heuristic ...
Keywords:
neural tensor network, search result diversification, relational learning to rank
13
April 2016
WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide Web
Publisher: International World Wide Web Conferences Steering Committee
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 12, Downloads (12 Months): 97, Downloads (Overall): 126
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Modeling and predicting retweeting dynamics in social media has important implications to an array of applications. Existing models either fail to model the triggering effect of retweeting dynamics, e.g., the model based on reinforced Poisson process, or are hard to be trained using only the retweeting dynamics of individual tweet, ...
Keywords:
mixture process, retweeting dynamics, popularity prediction
14
April 2016
WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide Web
Publisher: International World Wide Web Conferences Steering Committee
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 13, Downloads (12 Months): 161, Downloads (Overall): 227
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Recently, Deep Convolutional Neural Networks (CNNs) have been widely applied to sentiment analysis of short texts. Naturally, word embedding techniques are used to learn continuous word representations for constructing sentence matrix as input to CNN. As for sentiment analysis of customer reviews, we argue that it is problematic to learn ...
Keywords:
cnn, sentiment analysis, word embedding, online reviews
15
April 2016
WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide Web
Publisher: International World Wide Web Conferences Steering Committee
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 13, Downloads (12 Months): 100, Downloads (Overall): 135
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Link prediction over a knowledge graph aims to predict the missing entity h or t for a triple (h,r,t). Existing knowledge graph embedding based predictive methods represent entities and relations in knowledge graphs as elements of a vector space, and employ the structural information for link prediction. However, knowledge graphs ...
Keywords:
hierarchy, knowledge graph embedding, link prediction
16
March 2016
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP): Volume 24 Issue 3, March 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4, Downloads (12 Months): 34, Downloads (Overall): 49
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Sentiment classification aims to determine the sentiment polarity expressed in a text. In online customer reviews, the sentiment polarities of words are usually dependent on the corresponding aspects. For instance, in mobile phone reviews, we may expect the long battery time but not enjoy the long response time of the ...
Keywords:
topic model, cross-language, sentiment classification
17
February 2016
AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence
Publisher: AAAI Press
Matching natural language sentences is central for many applications such as information retrieval and question answering. Existing deep models rely on a single sentence representation or multiple granularity representations for matching. However, such methods cannot well capture the contextualized local information in the matching process. To tackle this problem, we ...
18
February 2016
AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence
Publisher: AAAI Press
Matching a question to its best answer is a common task in community question answering. In this paper, we focus on the non-factoid questions and aim to pick out the best answer from its candidate answers. Most of the existing deep models directly measure the similarity between question and answer ...
19
February 2016
AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence
Publisher: AAAI Press
Distributional hypothesis lies in the root of most existing word representation models by inferring word meaning from its external contexts. However, distributional models cannot handle rare and morphologically complex words very well and fail to identify some fine-grained linguistic regularity as they are ignoring the word forms. On the contrary, ...
20
February 2016
AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence
Publisher: AAAI Press
Matching two texts is a fundamental problem in many natural language processing tasks. An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score. Inspired by the success of convolutional neural network in image recognition, where neurons can capture many complicated patterns ...
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