Publication statistics

Pub. period:2007-2012
Pub. count:5
Number of co-authors:9


Number of publications with 3 favourite co-authors:

Christina Lioma:
Birger Larsen:
Qikai Cheng:



Productive colleagues

Wei Lu's 3 most productive colleagues in number of publications:

Christina Lioma:7
Laks V. S. Lakshma..:7
Birger Larsen:7

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Wei Lu


Publications by Wei Lu (bibliography)

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Lioma, Christina, Larsen, Birger and Lu, Wei (2012): Rhetorical relations for information retrieval. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012. pp. 931-940. Available online

Typically, every part in most coherent text has some plausible reason for its presence, some function that it performs to the overall semantics of the text. Rhetorical relations, e.g. contrast, cause, explanation, describe how the parts of a text are linked to each other. Knowledge about this so-called discourse structure has been applied successfully to several natural language processing tasks. This work studies the use of rhetorical relations for Information Retrieval (IR): Is there a correlation between certain rhetorical relations and retrieval performance? Can knowledge about a document's rhetorical relations be useful to IR? We present a language model modification that considers rhetorical relations when estimating the relevance of a document to a query. Empirical evaluation of different versions of our model on TREC settings shows that certain rhetorical relations can benefit retrieval effectiveness notably (>10% in mean average precision over a state-of-the-art baseline).

© All rights reserved Lioma et al. and/or ACM Press

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Lu, Wei, Cheng, Qikai and Lioma, Christina (2012): Fixed versus dynamic co-occurrence windows in TextRank term weights for information retrieval. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012. pp. 1079-1080. Available online

TextRank is a variant of PageRank typically used in graphs that represent documents, and where vertices denote terms and edges denote relations between terms. Quite often the relation between terms is simple term co-occurrence within a fixed window of k terms. The output of TextRank when applied iteratively is a score for each vertex, i.e. a term weight, that can be used for information retrieval (IR) just like conventional term frequency based term weights. So far, when computing TextRank term weights over co-occurrence graphs, the window of term co-occurrence is always fixed. This work departs from this, and considers dynamically adjusted windows of term co-occurrence that follow the document structure on a sentence- and paragraph-level. The resulting TextRank term weights are used in a ranking function that re-ranks 1000 initially returned search results in order to improve the precision of the ranking. Experiments with two IR collections show that adjusting the vicinity of term co-occurrence when computing TextRank term weights can lead to gains in early precision.

© All rights reserved Lu et al. and/or ACM Press

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Goyal, Amit, Lu, Wei and Lakshmanan, Laks V. S. (2011): CELF++: optimizing the greedy algorithm for influence maximization in social networks. In: Proceedings of the 2011 International Conference on the World Wide Web 2011. pp. 47-48. Available online

Kempe et al. [4] (KKT) showed the problem of influence maximization is NP-hard and a simple greedy algorithm guarantees the best possible approximation factor in PTIME. However, it has two major sources of inefficiency. First, finding the expected spread of a node set is #P-hard. Second, the basic greedy algorithm is quadratic in the number of nodes. The first source is tackled by estimating the spread using Monte Carlo simulation or by using heuristics [4, 6, 2, 5, 1, 3]. Leskovec et al. proposed the CELF algorithm for tackling the second. In this work, we propose CELF++ and empirically show that it is 35-55% faster than CELF.

© All rights reserved Goyal et al. and/or ACM Press

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Wu, Xuefeng, Lu, Wei and Jiang, Jiepu (2011): Journal evaluation using the importance of authors in co-authorship network. In: Proceedings of the 2011 iConference 2011. pp. 800-801. Available online

In this poster, we propose to evaluate journal influence based on journal authors' importance in co-authorship network. Preliminary results of evaluating Chinese LIS journals are presented.

© All rights reserved Wu et al. and/or ACM Press

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Lu, Wei, Zeng, Dinghao and Pan, Jingui (2007): QEM-Based Mesh Simplification with Effective Feature-Preserving. In: Shumaker, Randall (ed.) ICVR 2007 - Virtual Reality - Second International Conference - Part 1 July 22-27, 2007, Beijing, China. pp. 122-131. Available online

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