International Business Machines Corporation

Yoav Kantor

Roy N Bar-Haim

Lilach Eden

Noam Slonim

Yoav Avraham Katz

Naftali Liberman

Arie Cattan

An example system includes a processor to execute a key point analysis to extract key points from a number of input sentences. The processor can compute directional relation scores between the extracted key points. The processor can construct a key point graph based on the extracted key points and the directional relation scores. The processor can generate a key point graph visualization based on the key point graph.

Generating key point graphs using directional relation scores

A computing system, computer program product, and computer-implemented method for quantitative comment summarization are provided. The method includes receiving a collection of comments, identifying a set of candidate key points corresponding to the collection of comments, and selecting a subset of key points from the set of candidate key points, wherein the selected subset of key points includes key points that are most salient in the collection of comments. The method also includes automatically mapping each comment within the collection of comments to any corresponding key points within the subset of key points based on a match score between each comment and key point pair, as well as generating a summary including the subset of key points and an absolute number or percentage of the comments mapped to each key point.

Quantitative comment summarization

Combining predictions made by multiple different prediction systems, including: obtaining a new input sample; obtaining a combiner which comprises optimal selection values that are configured to maximize a predefined performance measure; automatically applying multiple different prediction systems to the new input sample, to generate predictions; and automatically selectively combining the generated predictions based on the optimal selection values, to generate a combined prediction whose predefined performance measure is improved compared to individual usage of each of the prediction systems. The selective combination includes splitting the generated predictions into an intersection subset, fully-disjoint subsets, and optionally one or more partially-disjoint subsets; selecting predictions, from the subsets, at a ratio corresponding to the optimal selection values associated with the subsets, and modifying the subsets to remove all non-selected predictions; and merging all predictions in the modified subsets, to produce the combined prediction.

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Haifa, Israel

Yoav Kantor