package(default_visibility = [":internal"])

licenses(["notice"]) # Apache 2.0

exports_files(["LICENSE"])

package_group(

name = "internal",

packages = [

"//textsum/...",

],

)

py_library(

name = "seq2seq_attention_model",

srcs = ["seq2seq_attention_model.py"],

deps = [

":seq2seq_lib",

],

)

py_library(

name = "seq2seq_lib",

srcs = ["seq2seq_lib.py"],

)

py_binary(

name = "seq2seq_attention",

srcs = ["seq2seq_attention.py"],

deps = [

":batch_reader",

":data",

":seq2seq_attention_decode",

":seq2seq_attention_model",

],

)

py_library(

name = "batch_reader",

srcs = ["batch_reader.py"],

deps = [

":data",

":seq2seq_attention_model",

],

)

py_library(

name = "beam_search",

srcs = ["beam_search.py"],

)

py_library(

name = "seq2seq_attention_decode",

srcs = ["seq2seq_attention_decode.py"],

deps = [

":beam_search",

":data",

],

)

py_library(

name = "data",

srcs = ["data.py"],

)

Sequence-to-Sequence with Attention Model for Text Summarization.

Authors:

Xin Pan ([email protected], github:panyx0718), Peter Liu ([email protected])

<b>Introduction</b>

The core model is the traditional seqeuence-to-sequence model with attention.

It is customized (mostly inputs/outputs) for the text summarization task. The

model has been trained on Gigaword dataset and achieved state-of-the-art

results (as of June 2016).

The results described below are based on model trained on multi-gpu and

multi-machine settings. It has been simplified to run on only one machine

for open source purpose.

<b>DataSet</b>

We used the Gigaword dataset described in

We cannot provide the dataset due to the license. See ExampleGen in data.py

about the data format. data/data contains a toy example. Also see data/vocab

for example vocabulary format. In <b>How To Run</b> below, users can use toy

data and vocab provided in the data/ directory to run the training by replacing

the data directory flag.

<b>Experiment Result</b>

8000 examples from testset are sampled to generate summaries and rouge score is

calculated for the generated summaries. Here is the best rouge score on

Gigaword dataset:

ROUGE-1 Average_R: 0.38272 (95%-conf.int. 0.37774 - 0.38755)

ROUGE-1 Average_P: 0.50154 (95%-conf.int. 0.49509 - 0.50780)

ROUGE-1 Average_F: 0.42568 (95%-conf.int. 0.42016 - 0.43099)

ROUGE-2 Average_R: 0.20576 (95%-conf.int. 0.20060 - 0.21112)

ROUGE-2 Average_P: 0.27565 (95%-conf.int. 0.26851 - 0.28257)

ROUGE-2 Average_F: 0.23126 (95%-conf.int. 0.22539 - 0.23708)

<b>Configuration:</b>

Following is the configuration for the best trained model on Gigaword:

batch_size: 64

bidirectional encoding layer: 4

article length: first 2 sentences, total words within 120.

summary length: total words within 30.

word embedding size: 128

LSTM hidden units: 256

Sampled softmax: 4096

vocabulary size: Most frequent 200k words from dataset's article and summaries.

<b>How To Run</b>

Pre-requesite:

Install TensorFlow and Bazel.

ls -R

.:

data textsum WORKSPACE

./data:

vocab test-0 training-0 training-1 validation-0 ...(omitted)

./textsum:

batch_reader.py beam_search.py BUILD README.md seq2seq_attention_model.py data

data.py seq2seq_attention_decode.py seq2seq_attention.py seq2seq_lib.py

./textsum/data:

data vocab

bazel build -c opt --config=cuda textsum/...

bazel-bin/textsum/seq2seq_attention \

--mode=train \

--article_key=article \

--abstract_key=abstract \

--data_path=data/training-* \

--vocab_path=data/vocab \

--log_root=textsum/log_root \

--train_dir=textsum/log_root/train

bazel-bin/textsum/seq2seq_attention \

--mode=eval \

--article_key=article \

--abstract_key=abstract \

--data_path=data/validation-* \

--vocab_path=data/vocab \

--log_root=textsum/log_root \

--eval_dir=textsum/log_root/eval

bazel-bin/textsum/seq2seq_attention \

--mode=decode \

--article_key=article \

--abstract_key=abstract \

--data_path=data/test-* \

--vocab_path=data/vocab \

--log_root=textsum/log_root \

--decode_dir=textsum/log_root/decode \

--beam_size=8

<b>Examples:</b>

The following are some text summarization examples, including experiments

using dataset other than Gigaword.

article: novell inc. chief executive officer eric schmidt has been named chairman of the internet search-engine company google .

human: novell ceo named google chairman

machine: novell chief executive named to head internet company

article: gulf newspapers voiced skepticism thursday over whether newly re - elected us president bill clinton could help revive the troubled middle east peace process but saw a glimmer of hope .

human: gulf skeptical about whether clinton will revive peace process

machine: gulf press skeptical over clinton 's prospects for peace process

article: the european court of justice ( ecj ) recently ruled in lock v british gas trading ltd that eu law requires a worker 's statutory holiday pay to take commission payments into account - it should not be based solely on basic salary . the case is not over yet , but its outcome could potentially be costly for employers with workers who are entitled to commission . mr lock , an energy salesman for british gas , was paid a basic salary and sales commission on a monthly basis . his sales commission made up around 60 % of his remuneration package . when he took two weeks ' annual leave in december 2012 , he was paid his basic salary and also received commission from previous sales that fell due during that period . lock obviously did not generate new sales while he was on holiday , which meant that in the following period he suffered a reduced income through lack of commission . he brought an employment tribunal claim asserting that this amounted to a breach of the working time regulations 1998 .....deleted rest for readability...

abstract: will british gas ecj ruling fuel holiday pay hike ?

decode: eu law requires worker 's statutory holiday pay

article: the junior all whites have been eliminated from the fifa u - 20 world cup in colombia with results on the final day of pool play confirming their exit . sitting on two points , new zealand needed results in one of the final two groups to go their way to join the last 16 as one of the four best third place teams . but while spain helped the kiwis ' cause with a 5 - 1 thrashing of australia , a 3 - 0 win for ecuador over costa rica saw the south americans climb to second in group c with costa rica 's three points also good enough to progress in third place . that left the junior all whites hopes hanging on the group d encounter between croatia and honduras finishing in a draw . a stalemate - and a place in the knockout stages for new zealand - appeared on the cards until midfielder marvin ceballos netted an 81st minute winner that sent guatemala through to the second round and left the junior all whites packing their bags . new zealand finishes the 24 - nation tournament in 17th place , having claimed their first ever points at this level in just their second appearance at the finals .

abstract: junior all whites exit world cup

decoded: junior all whites eliminated from u- 20 world cup